registration book07 · find out what your association is doing! come to the open meeting, meet your...

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July 29 to August 2, 2007

RegistrationBook

JSM2007

FIND OUT WHAT YOUR ASSOCIATION IS DOING!Come to the Open Meeting, meet your offi cers, hear about the following items, among others, and voice your opinions about the ASA:

➤ 2007 state of the Association – Mary Ellen Bock➤ Update on ASA fi nances – Sastry G. Pantula➤ Update from the Committee on Rewriting the ASA Strategic Plan – Robert Rodriquez➤ Introduction of Ronald Wasserstein, the incoming ASA executive director – William B. Smith➤ Summary of 2006 Board task forces – Sallie Keller-McNulty➤ Questions from the fl oor – Executive Committee

Please plan to attend and lend your voice to the discussion of important issues aff ecting the future of the ASA.

Mary Ellen Bock, ASA PresidentSunday, July 29, 2007, 6 p.m.Salt Palace Convention Center, 251D

American Statistical Association

OPEN MEETING

Joint Statistical Meetings, Salt Lake City, UtahWELCOMETABLE OF CONTENTS

WelcomeSalt Lake City, Utah, Information. ..........................................3

Travel Information .................................................................3

Keynote Speakers and Special Lectures ................................7

Map of Salt Lake City .........................................................64

Housing InformationGeneral Hotel Information ....................................................12

Housing Reservation Form ..................................................13

Hotel Map ..........................................................................13

Registration Add-OnsGeneral Add-On Information ................................................15

Continuing Education ...........................................................17

Speaker Luncheons & Coffee and Lunch Roundtables ..........33

Proceedings ........................................................................53

Tour Information ..................................................................55

Career Placement ServiceGeneral Career Placement Information ..................................57

Employer Registration Form .................................................58

Position Description Form.....................................................59

Applicant Registration Form ..................................................60

Applicant Information Form ..................................................61

RegistrationGeneral Registration Information ...........................................62

Early Bird and Advance Registration Form .............................63

Other EventsASA Open Meeting ....................................................... cover 2

EXPO 2007 ............................................................................5

IMS Presidential Address ......................................................14

IMS Student Mixer ................................................................14

SSC Reception .....................................................................16

ASA Longtime Member Reception ........................................22

Gertrude Cox Race ...............................................................27

First-Time Attendee Orientation and Reception ......................32

Opening Mixer ......................................................................34

Student Mixer .......................................................................40

ASA Presidential Address and Awards Session .....................42

Informal Dance Party ...........................................................45

ASA Booth ...........................................................................51

ASA Marketplace ..................................................................54

2 JOINT STATISTICAL MEETINGS 2007

JSM 2007 Program ChairAllan Rossman

California Polytechnic State University

International Biometric Society (ENAR)

Christopher S. CoffeyUniversity of Alabama at

Birmingham

International Biometric Society (WNAR)

Weng Kee WongUniversity of Los Angeles

Institute of Mathematical Statistics (Invited)

Mark LowThe Wharton School

University of Pennsylvania

Institute of Mathematical Statistics(Invited)Tony Cai

The Wharton SchoolUniversity of Pennsylvania

Institute of Mathematical Statistics (Contributed)Jiashun Jin

Purdue University

Statistical Society of Canada (SSC)X. Joan Hu

Simon Fraser University

Council of Chapters, ASAV. A. Samaranayake

University of Missouri-Rolla

Committee on Committees, ASAPatrick J. CantwellU.S. Census Bureau

General Methodology, ASAThomas H. Short

Indiana University of Pennsylvania

Section on Statistics and the Environment, ASA

Peter GuttorpUniversity of Washington

Section on Epidemiology, ASAJennifer Clark Nelson

Group Health Cooperative

Section on Government Statistics, ASA

Roberta L. SangsterBureau of Labor Statistics

Section on Statistical Graphics, ASA

Simon UrbanekAT&T Labs - Research

Section on Health Policy Statistics, ASA

Bonnie Ghosh-DastidarThe RAND Corporation

Section on Statistics in Marketing, ASA

Peter BoatwrightCarnegie Mellon University

Section on Nonparametric Statistics, ASA

Soumendra N. LahiriIowa State University

Section on Physical & Engineering Sciences, ASAWinson Taam

Boeing

Section on Quality & Productivity, ASA

William R. MyersProcter & Gamble

Section on Risk Analysis, ASADuane SteffeyExponent, Inc.

General Methodology, ASAElizabeth H. Slate

Medical University of South Carolina

Invited and Contributed PostersDongseok Choi

Oregon Health & Science University

Section on Bayesian Statistics, ASAMerlise A. ClydeDuke University

Biometrics Section, ASARunze Li

The Pennsylvania State University

Biopharmaceutical Section, ASAAmit Bhattacharyya

GlaxoSmithKline

Business & Economic Statistics Section, ASA

David A. DickeyNorth Carolina State University

Statistical Computing Section, ASAEdward J. Wegman

George Mason University

Section on Statistical Consulting, ASA

Phillip L. ChapmanColorado State University

Section on Statistics in Defense and National Security, ASA

Lara S. SchmidtThe RAND Corporation

Section on Statistical Education, ASA

Patti CollingsBrigham Young University

Social Statistics Section, ASAAllen L. Schirm

Mathematica Policy Research, Inc.

Section on Statistics in Sports, ASA

Mark E. GlickmanEdith Nourse Rogers Memorial Hospital

Section on Survey Research Methods, ASA

Steven G. HeeringaUniversity of Michigan Institute

for Social Research

Section on Teaching Statistics in the Health Sciences, ASA

Patrick TarwaterThe University of Texas Health

Science Center at Houston

2007 Program CommitteeAdvisory Committee on Continuing EducationKatherine T. Halvorsen, ChairSmith College

Eileen C. King, Vice Chair Procter & Gamble Company

Gordon J. Johnston SAS Institute, Inc.

Nandini Kannan The University of Texas at San Antonio

Ronald McRoberts North Central Research Station

Andy Mauromoustakos University of Arkansas

Xiaoming Sheng University of Utah

Charles Yun Tan Merck & Co., Inc

Clyde Tucker Bureau of Labor Statistics

ASA Continuing EducationRick PetersonEducation Programs Associate

ASA MeetingsElaine L. Powell, CMPAssistant Director of Meetings

Kathleen WertMeetings Planner

Donna R. ArringtonMeetings Planner

Kristen Campbell Meetings Coordinator

American Statistical Association 732 North Washington StreetAlexandria, VA 22314-1943Email: [email protected]

Web: www.amstat.org

No Photo Available

REGISTRATION BOOK 3

Joint Statistical Meetings, Salt Lake City, UtahWELCOME

ProceedingsEligibility guidelines and author instructions for JSM 2007 presenters are available at www.amstat.org/meetings/jsm/2007; click the “Program” tab and select “Proceedings.” The submission site will open August 1, 2007.

Spam FiltersConfirmations and other important information will be sent to you via email. Set any spam-blocking filters you have to allow emails sent from addresses containing “@amstat.org.”

AirportThe Salt Lake City International Airport (SLC) is just 15 minutes from downtown Salt Lake City. For more information, visit www.slcairport.com.

JSM Airline DiscountsUnited Airlines: Call (800) 521-4041 or visit www.united.com. Reference code 576EV. (If you are book-ing your ticket online, the code is case-sensitive, so use capital letters.)

Ground TransportationMost hotels provide complementary shuttle service to and from the airport. Other airport transportation options are Express Shuttle, a shared-ride service avail-able by calling (801) 596-1600; public buses; and taxis.

J oin the largest international gathering of stat-isticians in the world. Each year, the Joint Statistical Meetings offers five days of cut-

ting-edge presenters, technical sessions, round-tables with coffee or lunch, speaker luncheons, Continuing Education courses, computer technol-ogy workshops, and poster sessions, as well as the Career Placement Service, Exhibitor Expo, and Marketplace. Attendees network at several receptions and the cyber center and enjoy business, committee, and social meet-ings. Activities will take place at the Salt Palace Convention Center and The Grand America Hotel.

A rental car is recommended if you are planning excur-sions outside Salt Lake City.

Public TransportationFree Ride Zone for Buses and TrainsSalt Lake City’s Free Ride Zone includes major destina-tions, such as the Salt Palace Convention Center and Temple Square. Visit www.rideuta.com for details.

TRAX (cash payment only)$1.50 Adult One-Way/$0.75 Senior One-Way/Children under 5 ride FREE. Hours: 5:30 a.m.–11:00 p.m. Monday through Thursday, 5:30 a.m.–1:00 a.m. Friday and Saturday, and 9:30 a.m.–9:30 p.m. Sunday. For more information, visit www.rideuta.com or call (888) 743-3882.

UTA (cash payment only)$1.50 (one-way) for everyone ages 6 to 64/$0.75 for seniors (65+) and people with disabilities/children 5 and under ride FREE (limit two per paying adult). For more information, call (888) RIDE UTA.

BusesMost buses run from 6:00 a.m. until midnight on week-days. Saturday service is from 7:00 a.m. until midnight; Sunday service has limited regular routes (ski service runs during ski season only). Pay when you get on the bus. If you board within the downtown Free Ride Zone and leave the zone, pay when you get off. Correct change is required.

Register early (by June 21 for Early Bird rates) using the form on Page 63, or register online at www.amstat.org/meetings/jsm/2007/onlinereg. You’ll fi nd everything you need to sign up and ensure your spot at this year’s meetings, courses, workshops, and tours.


Rental CarsAVIS – (800) 331-1600 or www.avis.comAvis Worldwide Discount (AWD) Number: J099649JSM-negotiated rates are available from July 22, 2007, to August 9, 2007. All rates include unlimited free mileage. Weekend daily rates are available from noon Thursday until Monday at 11:59 p.m. (vehicle must be checked out by 3:00 p.m. Sunday).

Accessibility for People with DisabilitiesIf you have a disability that may impede your par-ticipation, please check the box on the Registration Form and attach a statement regarding your disabil-ity-related needs. Someone from the ASA Meetings Department will contact you prior to JSM to discuss them. Availability of appropriate accommodations cannot be ensured without prior notification.Salt Lake City Center facilities are accessible to patrons with disabilities. Salt Lake City takes pride in complying with the Americans with Disabilities Act. More information can be found at www.slcgov.com/ada/ADA.htm.

Advance RegistrantsThose who register in advance will need to show their confirmation letter and picture identification to receive registration materials.

WeatherAverage High: 92º F/25º CAverage Low: 62º F/15º CSummer in Salt Lake City is warm, but rarely humid; eve-nings can be cool. Dress in the city is relatively informal, so bring comfortable, lightweight business or casual clothes. Comfortable walking shoes for daytime leisure activities also are suggested. Hotels and meeting rooms are air-conditioned and can be cool, so long-sleeved shirts or light sweaters are recommended.

Time ZoneSalt Lake City is in the Mountain Daylight Time (MDT) Zone.

Wireless Internet AccessThe Salt Palace Convention Center has wireless inter-net access throughout the building for $15 per day.

Child CareWhile JSM will not have organized child care avail-able, services may be organized through Guardian Angels. Child care providers will come to your hotel room. The rate is $60 for a minimum of four hours of service for the first child, with an additional $1 per hour for each additional child. The fee for families that want to share a sitter is $2 more per hour for each family, or $5 more per hour for each family when children in diapers are involved. A $10 transportation fee is added to the total each time a sitter is called. For more information, call (206) 325-2327 or visit www.guardianangelbaby.com.The Caucus for Women in Statistics will provide a subsidy toward four hours of babysitting per family for up to 14 families. If you are interested, contact Tena I. Katsaounis, president of the caucus, at [email protected].

If You Are Not a Member...Information about the ASA, ENAR, WNAR, IMS, and SSC will be available at the society booths located in the registration area and exhibit hall of the Salt Palace Convention Center. Each society provides a variety of publications and activities to anyone interested in applied and/or theoretical statistics. Student member-ship is offered at substantially reduced rates.If you are not a member of the ASA, join now and receive a $15 discount on your first year of mem-bership. Join at the ASA Membership Booth in the registration area by Thursday, August 2, at 10 a.m. to receive your discount. This discount is valid for regular membership only. Ask about other discounted memberships for students, post-graduates, retirees, and developing country residents.

REGISTRATION BOOK 5

Addison-Wesley AllerganAmerican Statistical Association Amgen Inc.ASA-SIAM SeriesBiostatBlackwell PublishingBureau of Labor StatisticsBureau of Economic AnalysisCambridge University PressCapital OneCDC/ATSDRCOMSYSCRC Press - Taylor & FrancisCytel Inc.Duxbury, ThomsonEli Lilly and CompanyElsevierGE MoneyHawkes Learning SystemsINFORMSInsightful CorporationInstitute of Mathematical Statistics Internal Revenue Service (IRS) Statistics of IncomeJMP, a business unit of SASJSM 2008 Denver, Colorado

EXPO 2007 Sunday, July 29, 1 p.m.–6 p.m.Monday, July 30, 9 a.m.–6 p.m.Tuesday, July 31, 9 a.m.–6 p.m.Wednesday, August 1, 9 a.m.–2 p.m.

John Wiley & SonsJohnson & Johnson Family of CompaniesKforce Clinical Research StaffingMacKichan SoftwareMcGraw-Hill/IrwinMedFocus LLCMinitab Inc.National Center for Health Statistics (NCHS)NCSSOxford University PressPalisade CorporationPrentice HallProsoft Software, Inc.REvolution ComputingRTI InternationalSAGE PublicationsSalford SystemsSAS ApplicationSAS EducationSAS PublishingSIAM - Society for Industrial & Applied MathematicsSmith HanleySpringerSPSS Inc.Stat-Ease, Inc.Statistical Society of Canadastatistics.comStatPoint, Inc.StatSoft, Inc.Systat Software, Inc.The Cambridge Group Ltd.U.S. Department of EducationUSDA, National Agricultural Statistics Service (NASS)W.H. Freeman & CompanyWolfram ResearchXLSolutions Corporation


To reserve your Executive Suite, register online as soon as possible.Executive Suites are limited and have sold out in each of the last four years!

www.amstat.org/meetings/jsm/2007/placement

Each Executive Suite employer receives:

A PRIVATE, FURNISHED BOOTH for your exclusive use throughout the meeting. Use it as an offi ce, interview booth, or meeting space. It will give you the freedom to schedule interviews with potential employees whenever you like, without the need to reserve space on an hourly basis.

REGISTRATION FOR THE JSM PLACEMENT SERVICE, which includes up to 10 position listings. Also, up to fi ve representatives and three guests from your organization will have access for conducting onsite interviews.

ONLINE ACCESS TO APPLICANT DATA AND RÉSUMÉS IN ADVANCE. Beginning June 1 and continuing through September 30, search our online service for qualifi ed candidates based on specifi c criteria. Print résumés and pursue contacts before JSM starts, and continue to access this resource after the meeting for those last-minute openings.

AN ONSITE COMPUTER AND PRINTER IN YOUR SUITE. Eliminate waiting in line at the message center. Research and communicate with new applicants as they register.

SPECIAL RECOGNITION ONLINE AND ONSITE. Executive Suites are designated in the online listing of employers and noticed by candidates. Leave your prospective employees with a lasting impression of your company’s commitment to hiring talented statisticians. You also will receive JSM Partners Program credit for your purchase!

PERSONALIZED SERVICE from JSM Career Placement staff members, who will answer your questions and help with your interview traffi c.

Reserve an Executive Suite at the 2007 Joint Statistical Meetings and let us help you!Ar

e You

Seeking A Statistician?

Contact Amy Farris at [email protected] for more information.

Registration willremain open from May 1 through July 12.

REGISTRATION BOOK 7


President’s Invited Address Monday, July 30, 4 p.m.Regularization Methods in Statistical Model-Building: Statisticians, Computer Scientists, Classifi cation, and Machine LearningGrace Wahba is the I. J. Schoenberg-Hilldale Professor of Statistics at the University of Wisconsin-Madison and a mem-ber of the Computer Sciences Department and Department of Biostatistics and Medical Informatics. She is a member of the National Academy of Sciences and American Academy of Arts and Sciences. She also is a Fellow of the IMS, ASA, and American Association for the Advancement of Science. Since the early 70s, beginning with smoothing splines, she has been interested in regularization methods for nonparametric statistical model-building. Her recent research involves analysis of datasets where only noisy, incomplete dissimilarity information is available and looking for important patterns or clusters of interacting variables.

IMS Presidential Address Monday, July 30, 8 p.m.Open Access to Professional Information

Jim Pitman is the IMS president and professor of statistics and mathematics at the University of California, Berkeley. He has worked toward improving the quality and quantity of open-access content in the mathematical sciences by promoting and launching open-access journals for expository and survey material and developing open-source bibliographic software to encourage distributed alternatives to centrally controlled indexing systems. Recent projects include launching open-access expository journals Probability Surveys and Statistics Surveys and constructing open systems for navigation of online resourc-es in the mathematical sciences.

Deming Lecture Tuesday, July 31, 4 p.m.A Modern Framework for Enterprise ExcellenceDouglas C. Montgomery is professor of industrial and management systems engineering at Arizona State University. He is a Fellow of the American Society for Quality Control, ASA, and Institute of Industrial Engineers. He is a member of the honorary societies Phi Kappa Phi, Sigma Xi, Mu Sigma Rho, and Alpha Pi Mu. Montgomery’s professional interests include design of experiments, time series analysis and forecasting, and applications of linear models. He also is interested in opera-tions research and statistical methods applied to modeling and analyzing manufacturing systems.

Wald Lecture I Tuesday, July 31, 4 p.m.A Review of Some Surprises Encountered in Bayesian Model Selection

Wald Lecture II Wednesday, August 1, 10:30 a.m.Model Selection: Approximations and Multiplicities

Wald Lecture III Thursday, August 2, 10:30 a.m.Working with Invalid Models: the World of Computer Modeling

Jim Berger earned his PhD from Cornell University in 1974. He has served as president of the IMS, chair of the ASA’s Section on Bayesian Statistical Science, and president of the International Society for Bayesian Analysis. He also was awarded Guggenheim and Sloan Fellowships, the COPSS Presidents’ Award, and the Sigma Xi Research Award. Berger’s research has been in primarily Bayesian statistics, foundations of statistics, statistical decision theory, simulation, and model selection.

KEYNOTE SPEAKERS

REGISTRATION BOOK 9

ASA Presidential Address Tuesday, July 31, 8 p.m.Statistics: Harnessing the Power of InformationMary Ellen Bock is professor and head of the Department of Statistics at Purdue University in West Lafayette, Indiana. She is Fellow and president of the ASA and Fellow of the American Association for the Advancement of Science and IMS. Her areas of statistical research include applications in computational biology, bioinformatics, econo-metrics, and mathematical statistics.

COPSS Fisher Lecture Wednesday, August 1, 4 p.m.R. A. Fisher, Randomization, and Current Practice in Multicenter

Clinical TrialsMarvin Zelen, dubbed “father of biostatistics,” is professor of statistical science at Harvard School of Public Health. His path-breaking and original contributions are reflected in a number of published articles, book chapters, letters, editorials, and discussions on such topics as the design of experiments, design and analysis of clinical trials, randomization, length-biased sampling, screening methodologies for chronic diseases, and stochastic modeling with applications to cancer research. He is recognized as one of the pioneers of using Kronecker products and orthogonal projection operators in experimental design problems involving factorial and unbalanced designs. He also is known for his “play the winner rule” in randomized clinical trials, and his methods are still used in designing cutting-edge, multicenter clinical trials. Another of his passions, the early detection of disease, has lead to internationally recognized research on breast cancer screening, for which he was recently interviewed by CNN. Zelen is a Fellow of the ASA, American Association for the Advancement of Science, IMS, and International Statistical Institute and an elected member of the International Statistical Institute and American Academy of Arts and Sciences.

Rietz Lecture Sunday, July 29, 4 p.m.Statistical Problems of Gene MappingFor the last 10 years, David Siegmund has concentrated on statistical aspects of gene mapping. As a statistician also interested in probability theory, his research concentrates on statistical problems that arise in scientific applications and require novel probability theory for their resolution. Before 1985, his research concentrated on sequential analysis, with a primary focus on the design and analysis of sequential clinical trials.

Medallion Lecture I Sunday, July 29, 2 p.m.Modeling Genes: Statistical Challenges in Modern Genetics

Peter Donnelly is professor of statistical science at the University of Oxford. He is a Fellow of the IMS and Royal Statistical Society, a member of the International Statistical Institute, and an Honorary Fellow of the Institute of Actuaries. He has been awarded the Mitchell Prize of the ASA and International Society for Bayesian Analysis and the Guy Medal in Silver of the Royal Statistical Society. Donnelly’s early work was in applied probability, particularly stochastic models in genetics, but, for some years, his research has focused on genetics. He played a major role in the HapMap project, an international collaboration that followed the Human Genome Project in studying genetic diversity in worldwide popula-tions. He currently chairs a collaboration of 25 UK research groups studying 12 common human diseases.

IMS Special Lectures


Medallion Lecture II Monday, July 30, 10:30 a.m.Understanding Ecological CommunitiesClaudia Neuhauser is HHMI professor and head of the Department of Ecology, Evolution, and Behavior at the University of Minnesota, Twin Cities. Her work is at the interface of ecology and evolution, as she investigates effects of spatial structure on community dynamics; in particular, the effect of competition on the spatial structure of competitors and the effect of symbionts on the spatial distribution of their hosts. In addition, her research in population genetics has resulted in the devel-opment of statistical tools for random samples of genes. She is currently director of an NSF-funded grant on nonequilibrium dynamics across space and time, which provides interdisciplinary education and training to graduate students from ecology, geology, civil engineering, and computer science.

Medallion Lecture III Tuesday, July 31, 8:30 a.m.Functional Regression Analysis: Models, Methods, and Applications

Hans-Georg Müller is professor of statistics at the University of California, Davis. Among his current research inter-ests are the theory and methodology of high-dimensional and functional data analysis and applications in biodemography, genomics, and finance. He is a member of the International Statistical Institute and a Fellow of the ASA, IMS, and American Association for the Advancement of Science.

Medallion Lecture IV Wednesday, August 1, 8:30 a.m.Quantile Regression under CensorshipXuming He is professor of statistics at the University of Illinois, Urbana-Champaign. He is a Fellow of the ASA and IMS. His primary research interests in statistics include robust methods, semi/nonparametric modeling, large-sample theory, quan-tile regression, dimension reduction, and resampling methods. His interdisciplinary research spans genomics, epidemiology, educational testing, dysphagia research, and atmospheric studies. He is currently the IMS Bulletin editor and serves on the editorial boards of Annals of Statistics and JASA.

Medallion Lecture V Wednesday, August 1, 2 p.m.Joint Modeling of Longitudinal and Survival Data

Jane-Ling Wang is professor of statistics and graduate adviser of the biostatistics program at the University of California, Davis. She has served on various committees for the ASA, International Chinese Statistical Association, IMS, and the Bernoulli Society. She is currently president-elect of the International Chinese Statistical Association. Wang’s research areas include aging and longevity, biodemography, dimension-reduction methods, functional and longitudinal data analysis, joint modeling of longitudinal and survival data, and survival analysis. She is a Fellow of the ASA and IMS and an Elected Member of the International Statistical Institute.

REGISTRATION BOOK 11

ONLINE2007 PROGRAM

The Preliminary program will NOT appear in the May issue of Amstat News, but will be available online at http://www.amstat.org/meetings/jsm/2007/OnlineProgram

starting on March 26, 2007.

New This Year Starting May 1, 2007, you will be able to download or print a PDF version of the program. This preliminary program will be updated weekly until the final program is posted on July 9, 2007. When you arrive in Salt Lake City, Utah, make sure to refer to the final program and the program errata sheet or check the online program on the web site for a current version.

The FULL program for JSM 2007 is at

www.amstat.org/meetings/jsm/2007.


Please check individual hotel web links for detailed information about the amenities at each property. Handicap-accessible rooms, rollaway beds, cribs, and connecting rooms may be available by request.

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1The Grand America Hotel, 555 South Main Street(300 premier rooms/75 executive suites),www.grandamerica.com

✔ ✔ ✔ ✔ ✔✔ F ✔ ✔ ✔

✔ V $P $

✔✔ F

2The Little America, 500 South Main Street (300 garden rooms, 310 tower rooms, 100 govt. rooms), www.littleamerica.com/slc

✔ ✔ ✔ ✔ ✔✔ V $ P F

✔✔ F

3Radisson Hotel Salt Lake City Downtown, 215 West South Temple (251 rooms, 20 govt. rooms),www.radisson.com/saltlakecityut_downtown

✔ ✔ ✔ ✔ ✔ ✔ ✔✔ F

✔ F ✔ ✔ ✔

✔ V $ P $

✔ ✔✔ X $

4Salt Lake City Marriott Downtown, 75 South West Temple (200 rooms, 50 govt. rooms),http://marriott.com/property/propertypage/SLCUT

✔ ✔ ✔ ✔ ✔ ✔ ✔✔ $

✔ $ ✔ ✔ ✔

✔ V $ P $

✔ ✔✔ X $

5Shilo Inn Suites Hotel, 206 South West Temple(150 rooms, 38 govt. rooms), www.shiloinns.com/Utah/saltlakecity.html

✔ ✔ ✔ ✔ ✔ ✔ ✔✔ F

✔ F ✔ ✔ ✔

✔ P F ✔ ✔

✔ F

6 Hilton Salt Lake City Center, 255 South West Temple (200 rooms, 20 govt. rooms), www.hilton.com

✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔✔V $P $

✔ ✔✔ X $

7Salt Lake City Marriott City Center, 220 South State Street (135 rooms, 15 govt. rooms),http://marriott.com/property/propertypage/SLCCC

✔ ✔ ✔ ✔ ✔ ✔ ✔✔ F ✔ ✔

✔ V $ P $

✔ ✔✔ X $

8 Sheraton City Center Salt Lake City, 150 West 500 South (200 govt. rooms ONLY), www.saltlakecitysheraton.com

✔ ✔ ✔ ✔ ✔ ✔ ✔✔ $ ✔ ✔

✔ V $ P $

✔ ✔✔ F

9Red Lion Salt Lake Downtown, 161 West 600 South (100 rooms), http://redlion.rdln.com/HotelLocator/HotelOverview.aspx?metaID=43

✔ ✔ ✔ ✔ ✔ ✔ ✔✔ F ✔ ✔ ✔

✔ P F ✔ ✔

✔ F

10 Best Western Garden Inn, 154 West 600 South (200 student rooms, 40 govt. rooms), www.bwgardeninn.com

✔ ✔ ✔ ✔ ✔ ✔ ✔✔ F ✔ ✔ ✔

✔ P F ✔ ✔

✔ F

Key: ✔ = available; P = self-parking; V = valet parking; F = free; $ = additional fee required; X = Express Shuttle

JSM 2007 GENERAL HOTEL INFORMATIONAll rooms are subject to a 12.7% sales tax (subject to change). CUT-OFF IS JULY 2, 2007.

Hotel Information and Amenities

AVAILABILITY: Hotel choices will be honored based on the requested hotel’s availability. Should all choices be sold out, an alternate hotel will be assigned, unless other provisions are made on your housing form. The JSM Housing Bureau will continue to process reservations as long as inventory is available through the cut-off date. Reserve early to avoid delays due to heavy volume during the week of the deadline.CHECKIN TIME is generally 3:00 p.m.; check-out time is generally noon.All suite requests must be approved in advance by the ASA Meetings Department. Please send an email with suite request information to [email protected].

RATES Single/Double Triple/Quad Government (valid govt. ID at check-in) Suites

1 The Grand America Hotel $185/$185–Premier$202/$202–Exec. Suite

$205/$225–Premier$222/$242–Exec. Suite None available $202–$242

2 The Little America $150/$150–Garden$167/$167–Tower

$168/$180–Garden$182/$197–Tower $90/$110–Courtside $202–$242

3 Radisson Hotel Salt Lake City Downtown $135/$135 $90/$110/$130/$150 TBD

4 Salt Lake City Marriott Downtown $144/$144 $144/$144 $90/$90/$90/$90 TBD

5 Shilo Inn Suites Hotel $120/$120 $130/$130 $90/$90 TBD

6 Hilton Salt Lake City Center $149/$149 $164/$179 $90/$105 TBD

7 Salt Lake City Marriott City Center $139/$139 $149/$159 $90/$90/$109/$129 $299–$999

8 Sheraton City Center Salt Lake City $139/$139 $149/$159 $90/$90 $219–$799

9 Red Lion Salt Lake Downtown $110/$110 $120/$130 $90/$110 $295

10 Best Western Garden Inn(Student & Government Only) $74/$86 $98/$110 $90/$90 $159

$145/$145


Company __________________________________________________________

Address ___________________________________________________________

City _________________________________________State _________________

Country _______________________________ZIP/Postal Code________________

Daytime Phone _________________________Fax __________________________

PAYMENT INFORMATION: ❏ Check enclosed (made payable to JSM Housing Bureau)

❏ VISA ❏ MasterCard ❏ American Express ❏ Diners Club ❏ Discover Card

Credit Card Number_________________________________________________

Exp. Date_________________________________________________________

Name of Cardholder_________________________________________________

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DEPOSIT: All reservation requests must be accompanied by a credit card guarantee or check for one night’s deposit. Housing forms received without a valid guarantee/deposit will not be processed. Faxed requests must include a valid credit card. Check deposits must be mailed with a completed housing form by July 2, 2007. Checks must be in U.S. dollars and made payable to the JSM Housing Bureau. Credit cards will be charged only if the reservation is cancelled within the penalty period.

CONFIRMATION: Confirmations will be mailed, faxed, or emailed within one week of pro-cessing your reservation. You will not receive a confirmation from your hotel. Please contact the JSM Housing Bureau via [email protected] if you do not receive your confirmation in seven days.

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CHANGES: Prior to July 19, all changes, cancellations, etc., must be made by either telephone, web, or in writing via fax or email to the JSM Housing Bureau at [email protected]. After this date, changes may be made directly with the hotel. You must cancel within 72 hours of your expected arrival date, or one night’s room and tax will be charged.

CANCELLATIONS: After July 2, all cancellations will be charged a $25.00 Event Cancellation Fee. All cancellations within 72 hours prior to day of arrival will result in forfeiture of one night’s room and tax. Early departures may be subject to penalty fees set by the hotel. Credit cards will be charged only if reservations are cancelled within the penalty period. A charge of first night’s room and tax will be applied and/or forfeited if you do not cancel or arrive on your scheduled arrival date.

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HOUSING INFORMATION AND RESERVATIONS INSTRUCTIONS2007 Joint Statistical Meetings • ASA-ENAR-WNAR-IMS-SSC • Salt Lake City, Utah • July 29– August 2

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Joint Statistical Meetings, Salt Lake City, UtahWELCOMEREGISTRATION ADD-ONS

Continuing Education Courses and Computer Technology WorkshopsThe Advisory Committee on Continuing Education is offering a number of courses, and JSM vendors will present Computer Technology Workshops using their latest software.

Speaker with LunchSpeaker luncheon tickets are listed on the registration form; tickets will be sold onsite until 2 p.m. the day before the scheduled luncheon. Kosher and heart healthy meals are available only for those who preregister and purchase tick-ets at that time. Regular and vegetarian meals will be avail-able for those who preregister or purchase tickets onsite.

Roundtables with Coffee or LunchFor great discussion and a networking event that doesn’t bust your wallet, register for a roundtable with coffee, offered Monday through Wednesday from 7:00 a.m.–8:15 a.m. Tickets are just $12 and listed on the Registration Form. If early morning isn’t your style, roundtables with lunch also offer great discussion and networking opportunities and are held Monday through Wednesday from 12:30 p.m.–1:50 p.m. Tickets are $40 and listed on the Registration Form. Menus for the roundtables can be found near their descrip-tions, starting on Page 33. Tickets also will be sold onsite until 2 p.m. the day before the scheduled roundtables.

Guest BadgesGuest badges are available for $20. All guests 18 and older must purchase a badge to visit the exhibit hall and attend the Sunday Opening Reception (open bar with beer and wine) and Tuesday dance party (cash bar). Guest registration does not include technical session attendance. Dependent chil-dren, 17 years old and younger attending with a parent, may visit the exhibit hall without a badge.

Tours and AttractionsMost tours are limited in size, so reserve tickets early. Tickets must be purchased by July 12, 2007, to guarantee availability. There is no guarantee of ticket availability onsite. Once a tour is sold out, no additional buses will be available. The ASA reserves the right to cancel tours with low advance registration. For additional information about local attractions, click on the “Conference Information” tab, then select “Local Information and Travel” at www.amstat.org/meetings/jsm/2007.

Courses, workshops, roundtable discussions, guest badges, and tours are available at additional cost. If you have questions, call (866) 421-7169 or email [email protected]. We regret we cannot accept registrations by telephone or email.

Joint Statistical Meetings, Salt Lake City, UtahWELCOMECONTINUING EDUCATION


RegistrationThe registration deadline for courses and Computer Technology Workshops is 11:59 p.m. EDT on July 12, 2007. Registration will depend on seat availability and be handled on a first-come, first-served basis. If seats are available after the July 12 deadline, onsite registration will be offered. To participate in courses and Computer Technology Workshops, you must register for JSM.

TextbooksSome instructors recommend textbooks. If a course attendee wishes to obtain the textbook, he or she must order it from the publisher or other vendor. The ASA no longer orders texts for purchase. Textbook infor-mation is provided with the course descriptions.

Cancellation PolicyCancellations received by 11:59 p.m. EDT on June 21, 2007, will receive an 80% refund. Cancellations received June 22–July 12 will receive a 60% refund. Cancellations received after July 12 will not be refund-ed. The ASA reserves the right to amend the syllabi and/or cancel courses and workshops. Should a can-cellation occur, tuition will be refunded or applied to another course or workshop, if seating is available. Cancellation notices will be emailed to participants whose registrations are received by July 12, 2007.

Course Participation CertificatesThe ASA provides course participation certificates upon request. To receive a certificate, you must com-plete a request form at the completion of the course. Your certificate will be mailed to you within one month of the close of JSM. Be sure to indicate the title and number of each course for which you want a cer-tificate. You must attend the entire course to qualify.

Excellence-in-CE AwardEach year, the Advisory Committee on Continuing Education selects a course offered the previous year that exceeded expectations in quality, content, and presenta-tion. The ACCE recognizes this by inviting the course back the following year and presenting the instructor with the Excellence-in-CE Award. These courses are noted with a % in the list of course descriptions.

Continuing Education offerings consist of courses (e.g., CE_07C) and Computer Technology Workshops (e.g., CE_34T). Courses are offered in two-day, one-day, and half-day formats Saturday through Tuesday. Computer Technology Workshops are offered in two-hour intervals on Wednesday. An hour-and-a-half break, beginning at 12:30 p.m., is provided for attendees to have lunch on their own. The ASA provides beverages for mid-morning and mid-afternoon CE course breaks.


Continuing Education at a glance

Saturday, July 28, 20078:30 a.m.–5:00 p.m. CE_01C David Spiegelhalter Bayesian Modeling in Practice

8:30 a.m.–5:00 p.m. CE_02C Garrett Fitzmaurice Applied Longitudinal Analysis %

8:30 a.m.–5:00 p.m. CE_03C Dallas E. Johnson Design and Analysis of Crossover Experiments

8:30 a.m.–5:00 p.m. CE_04C Paul Biemer Latent Class Analysis of Survey Error

8:30 a.m.–5:00 p.m. CE_05C Richard Cook/Jerry Lawless Statistical Methods for the Analysis of Recurrent Events

8:30 a.m.–5:00 p.m. CE_06C Kimberly Crimin/Thomas Vidmar Nonclinical Statistics for Drug Discovery

8:30 a.m.–5:00 p.m. CE_07C Antony Unwin/Heike Hofmann Graphics of Large Datasets

Sunday, July 29, 20078:30 a.m.–5:00 p.m. CE_01C David Spiegelhalter Bayesian Modeling in Practice

8:00 a.m.–12:00 p.m. CE_08C Naitee Ting/James MacDougall Dose-Finding in Drug Development

8:30 a.m.–5:00 p.m. CE_09C Oliver Schabenberger Generalized Linear Mixed Models: Theory and Applications

8:30 a.m.–5:00 p.m. CE_10C Margaret S. Pepe/Holly Janes/Todd Alonzo

Statistical Evaluation of Medical Tests and Biomarkers for Classification

8:30 a.m.–5:00 p.m. CE_11C Jay Breidt/Jean Opsomer Modeling and Data Analysis for Complex Surveys

8:30 a.m.–5:00 p.m. CE_12C Jerome Sacks/William J. Welch A Practical Guide for the Design and Analysis of Virtual (Computer Model) Experiments

8:30 a.m.–5:00 p.m. CE_13C Thomas Herzog/ Fritz Scheuren/ William Winkler

Data Quality and Record Linkage Techniques

1:00 p.m.–5:00 p.m. CE_14C Christopher S. Coffey/Brenda Gaydos/José Pinheiro

Adaptive Dose-Response Studies

Monday, July 30, 20078:00 a.m.–12:00 p.m. CE_15C Charles S. Davis Categorical Data Analysis

8:30 a.m.–5:00 p.m. CE_16C Peter H. Westfall Multiple Comparisons and Multiple Tests

8:30 a.m.–5:00 p.m. CE_17C Christy Chuang-Stein/Alex Dmitrienko/Geert Molenberghs

Analysis of Clinical Trials: Theory and Applications

8:30 a.m.–5:00 p.m. CE_18C Howard S. Burkom/David Banks Temporal Alerting Algorithms for Biosurveillance

8:30 a.m.–5:00 p.m. CE_19C Peter F. Thall Practical Bayesian Clinical Trial Design

8:30 a.m.–5:00 p.m. CE_20C Wei-Yin Loh Classification and Regression Trees

1:00 p.m.–5:00 p.m. CE_21C Ingram Olkin Meta-analysis: Statistical Methods for Combining the Results of Independent Studies

Tuesday, July 31, 20078:00 a.m.–12:00 p.m. CE_22C Tamraparni Dasu/Simon Urbanek Harnessing Data Streams through Statistical Computing

8:30 a.m.–5:00 p.m. CE_23C Michael Proschan Statistical Monitoring of Clinical Trials: a Unified Approach

8:30 a.m.–5:00 p.m. CE_24C Michael J. Daniels/Joe Hogan Dropout in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity

8:30 a.m.–5:00 p.m. CE_25C Kenneth Lange/Janet Sinsheimer/Eric Sobel

Statistical Genetics

8:30 a.m.–5:00 p.m. CE_26C Marina Vanucci/Brani Vidakovic Wavelets and Statistical Applications

8:30 a.m.–5:00 p.m. CE_27C Danyu Lin Analysis of Censored Data

1:00 p.m.–5:00 p.m. CE_28C Tim Hesterberg Bootstrap Methods and Permutation Tests for Doing and Teaching Statistics

Time Course Instructor(s) Course Title


CE_01C (two-day course) 8:30 a.m.–5:00 p.m.Bayesian Modeling in PracticeInvited Two-DayInstructor: David Spiegelhalter

This course will deal with the practical aspects of Bayesian mod-eling, not only in terms of getting results out, but also in dealing with difficult strategic questions. A range of applications will be used to illustrate the implementation of models of varying com-plexity, and we will try to provide tentative guidance on some of the more tricky aspects of Bayesian analysis. A particular aim is to show how we can acknowledge and explicitly include in a model realistic assumptions about potential inadequacies in the available data. Examples will be illustrated using WinBUGS. Attendees should be familiar with basic probability theory and common distributions, as well as standard statistical concepts, such as linear and nonlinear regression, generalized linear models, and random-effects modeling. A basic familiarity with Bayesian methods and WinBUGS also would be helpful.

FEES: M–$575 ($735), NM–$700 ($865), S–$340 ($550)

CE_02C % 8:30 a.m.–5:00 p.m.Applied Longitudinal Analysis2006 Excellence-in-CE Award WinnerInstructor: Garrett Fitzmaurice

This course will provide an introduction to statistical methods for analyzing longitudinal data. The emphasis will be on the practical, rather than theoretical, aspects of longitudinal analysis. We will begin with a review of established methods for analyzing longitudinal data when the response of interest is continuous. A general introduction to linear mixed effects models for continu-ous responses will be presented. We will then present an over-view of two main types of models—marginal and generalized linear mixed models—used when the response of interest is cat-egorical. We will highlight the main distinctions between these models and discuss the types of scientific questions addressed by each. Attendees should have a strong background in linear regression and minimal exposure to generalized linear models (e.g., logistic regression).

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_03C 8:30 a.m.–5:00 p.m.Design and Analysis of Crossover ExperimentsCosponsor: Biopharmaceutical SectionInstructor: Dallas E. Johnson

Crossover designs are a special type of repeated measures experi-ment where the experimental units are given different treat-ments in different sequences over time. They offer advantages over traditional designs when comparing different treatments, as crossover designs allow each experimental unit to serve as its own control. There are, however, certain pitfalls that must be avoided if crossover designs are going to be used effectively. This course is intended for those involved with analyzing certain kinds of messy experiments that involve crossover designs with ordinal and/or continuous data. The course will introduce the important issues associated with crossover experiments and provide instructions for using statistical packages, such as SAS and SPSS, to analyze crossover experiments correctly with and without carryover effects.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_04C 8:30 a.m.–5:00 p.m.Latent Class Analysis of Survey ErrorCosponsor: Section on Survey Research MethodsInstructor: Paul Biemer

This course will present a statistical framework for modeling and estimating classification error in surveys. We will examine early models for survey measurement error and demonstrate their similarities, strengths, and weaknesses. We will then cast these models in a general latent class modeling (LCM) framework where the true values of a variable are assumed to be unobserved (latent) and a survey response constitutes a single indicator of the latent variable. We will discuss methods for estimating the model parameters and issues of model identifiability, and examples and illustrations will be presented to demonstrate the estimation methods and interpretation of the latent class analysis results. The utility of the models for evaluating and improving survey data quality also will be discussed and demonstrated. The course will introduce attendees to the ℓEM software for fitting a wide range of LCMs. The software can be downloaded from the web at no charge.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

Saturday, July 28Continuing Education

The ASA no longer orders texts for purchase. Textbook information is provided with the course descriptions.

M=Member NM=Nonmember S=Student(Price in parentheses is for onsite registration.)


CE_05C 8:30 a.m.–5:00 p.m.Statistical Methods for the Analysis of Recurrent EventsInstructors: Richard Cook and Jerry Lawless

Recurrent event data arise in fields such as public health, actuarial science, social science, economics, business, and manufacturing. The aim of this course is to introduce a variety of models and statistical methods available for the analysis of recurrent event data. Models for the analysis of count data, gap time models, and intensity-based models will be discussed, as well as robust methods based on rate and mean functions. The emphasis will be on multiplicative models. Techniques for model assessment will be discussed. Features of the models will be illustrated by application to several examples from health research and reli-ability. Statistical analysis will be carried out using R/S-PLUS code. Some familiarity with basic methods of survival analysis is required.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_06C 8:30 a.m.–5:00 p.m.Nonclinical Statistics for Drug DiscoveryInstructors: Kimberly Crimin and Th omas Vidmar

This course will provide an opportunity for new and experienced statisticians to enhance their statistical tools and improve their consulting skills. As communication is the most important asset of a nonclinical statistician, the course will begin with a discussion of the consulting aspect of the statistician in drug discovery. We also will discuss the scientific questions, statistical hypotheses, and statistical methodologies used in

high-throughput screening, lead-finding animal experiments, drug safety, pharmaceutical sciences, chemometrics, and genomics. In each area, the role of the consulting statistician will be emphasized. Attendees should have a good understanding of linear models and multivariate methods and familiarity with Applied Linear Statistical Models by John Neter, Michael H. Kutner, William Wasserman, and Christopher J. Nachtsheim. Definitions for scientific terms will be provided.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_07C 8:30 a.m.–5:00 p.m.Graphics of Large DatasetsCosponsor: Section on Statistical GraphicsInstructors: Antony Unwin and Heike Hofmann

This course discusses how to look at ways of visualizing large data-sets, whether large in numbers of cases, in numbers of variables, or both. Data visualization is useful for data cleaning, exploring data, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. It is essential for exploratory data analysis and data mining. Anyone who has to explore a large dataset of their own should benefit from attending this course. Attendees should have knowledge of standard statisti-cal graphics and experience carrying out data analysis.

Recommended Textbook: Unwin, A.R.; Theus, M.; and Hofmann, H. (2006). Graphics of Large Datasets. Springer. ISBN: 9780387329062.FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

Student OpportunitiesOpportunities› Reduced JSM Registration Fee of $50

› Reduced Fees for Continuing Education and the Career Placement Service

› Free Student Mixer

› Cox Scholarship Fun Run/Walk

› State-of-the-Art Exhibit Hall

› Networking Opportunities with Renowned Statisticians and Other Students

› Technical Presentations

› ASA Membership for only $10! Join at the Membership Desk near Registration.


CE_01C (two-day course) 8:30 a.m.–5:00 p.m.See Saturday, July 28, for details.

CE_08C 8:00 a.m.–12:00 p.m.Dose-Finding in Drug DevelopmentCosponsor: Biopharmaceutical SectionInstructors: Naitee Ting and James MacDougall

For dose-finding study designs, the thinking process should start way before a drug candidate enters Phase II. Scientists need to make best use of data obtained from preclinical experiments and early Phase I trials, learn from other drugs of the same class, and understand the PK and PD properties of the drug candidate. It is also important to consider the formulation, potential market environment, and similar drugs that may compete with the candidate under study. After the dose response clinical data are collected, many statistical approaches are available to perform data analysis. The two main categories are modeling approaches and multiple comparison adjustments. Depending on stage of development and objectives of the study, appropriate method will be selected. The usefulness of each approach under various situations will be discussed in this course.

FEES: M–$210 ($285), NM–$275 ($345), S–$125 ($200)

CE_09C 8:30 a.m.–5:00 p.m.Generalized Linear Mixed Models: Theory and ApplicationsInstructor: Oliver Schabenberger

Attendees of this course will discuss the theory of generalized linear mixed models and the application of these models. The course consists of two parts. Part I covers the requisite theory of generalized linear mixed models. Part II covers examples and applications and adds additional theoretical detail as needed; it is the majority of the course. The first part of the workshop makes the connection between linear models (LM), generalized linear models (GLM), linear mixed models (LMM), and general-ized linear mixed models (GLMM) in terms of model formula-tion, distributional properties, and approaches to estimation. Participants learn that GLMMs are an encompassing family of models and come to understand the differences and similarities in approaches to estimation and inference within the class. We will discuss the pros and cons of various estimation approaches and describe their implementation with SAS/STAT® software. The first part of the course ends with a discussion of over-arching issues the analyst must confront when working with correlated,

non-normal data. The second part uses a variety of examples to revisit the theory taught in Part I, develop new insights (e.g., low-rank mixed model smoothing), and present applications from different disciplines. A final section describes inferential proce-dures following parameter estimation. Computations are based on the mixed model tools in SAS/STAT software, primarily the GLIMMIX and NLMIXED procedures.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_10C 8:30 a.m.–5:00 p.m.Statistical Evaluation of Medical Tests and Biomarkers for Classifi cationCosponsor: Section on Statistics in EpidemiologyInstructors: Margaret S. Pepe, Holly Janes, and Todd Alonzo

This course will cover estimation and comparison of receiver operating characteristic (ROC) curves. We will first describe extensions to adjust for covariates that affect biomarker/test measurements. For assessing factors associated with test per-formance, ROC regression methods will be presented. We also will consider how to evaluate the added benefit of a new test when standard tests or clinical variables already exist. Second, we will consider the design of case-control studies that are most common in this field. Sample size calculations and optimal choice of case-control ratio will be presented. The attributes and limitations of matching controls to cases will be discussed. Third, prospective studies will be considered. They are often subject to restrictions on ascertainment of the gold standard outcome vari-able. Finally, we will discuss problems incurred when the gold standard reference test is subject to error. A new suite of freely available Stata programs will implement analyses.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_11C 8:30 a.m.–5:00 p.m.Modeling and Data Analysis for Complex SurveysCosponsors: Section on Statistics and the Environment and Survey Research Methods SectionInstructors: Jay Breidt and Jean Opsomer

This short course is aimed at researchers with a basic back-ground in statistical theory (elementary probability, sampling properties of estimators, likelihood) and methods (point and interval estimation, hypothesis testing, regression analysis) who need to analyze complex survey data. No previous background in survey sampling is assumed. We will review the features that

Sunday, July 29Continuing Education




make survey data complex, including design properties and post-sampling adjustments. We also will describe and compare model-based and design-based approaches to estimation and inference with complex survey data, review available software, and illustrate with example datasets.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_12C 8:30 a.m.–5:00 p.m.A Practical Guide for the Design and Analysis of Virtual (Computer Model) ExperimentsCosponsor: Section on Quality and ProductivityInstructors: Jerome Sacks and William J. Welch

Computer models, or “codes,” are used throughout science and engineering to further understanding of fundamental processes as replacements for time-consuming, costly, or unfeasible physi-cal experiments and as tools for developing and designing prod-ucts and policy decisions. A virtual experiment with a computer model involves making runs of the code according to a plan. Analysis of the output data from runs of the code requires sta-tistical methodology that can address questions of high dimen-sionality (many model inputs); small n (few runs); and unknown, nonlinear, complex relationships between inputs and outputs. In the last 20 years, a systematic approach has emerged that treats these issues of experimental design and data analysis in the con-text of deterministic models (i.e., computer models that produce the same output if the inputs are repeated). The purpose of this

course is to describe these methods and provide a practical guide to their use, exemplified by explicit applications in engineering, science, and policymaking. Attendees should be acquainted with response surface methods and language as typified in Introduction to Linear Regression Analysis by D. C. Montgomery, E. A. Peck, and G. G. Vining.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_13C 8:30 a.m.–5:00 p.m.Data Quality and Record Linkage TechniquesInstructors: Th omas Herzog, Fritz Scheuren,and William Winkler

This course is based on the book Data Quality and Record Linkage Techniques. The course will provide practical advice, mathematical rigor, management insight, and philosophy. The intended audience is the working analyst, whether a survey statistician, census taker, or business consultant. We will employ-real life examples, using illustrations from our successful and not-so-successful practice, though a few will be contrived to make a point. A main goal is to aid practitioners in achiev-ing a deeper understanding, at an applied level, of the issues involved in improving data quality through editing, imputation, and record linkage. We will begin with examples of quality suc-cesses and failures, motivating techniques to be gone over later. Basic editing techniques will be discussed next, beginning with a short history, but with more-advanced editing and imputation techniques being covered as well. The heart of the course is our presentation of record linkage techniques. These, unlike most editing and imputation techniques, often can lead to real data quality improvements, rather than just mitigating the negative consequences of data errors.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_14C 1:00 p.m.–5:00 p.m.Adaptive Dose-Response StudiesInstructors: Christopher S. Coff ey, Brenda Gaydos,and José Pinheiro

Insufficient understanding of the dose response profile of a compound is a shortcoming of clinical drug development, often leading to incorrect dose selection for the confirmatory phase. Indeed, failure to characterize adequate dosing early is often cited as a key contributor to the high late-stage attrition rate currently faced by the pharmaceutical industry. Adaptive dose-response trials allow more efficient learning about the dose response ear-lier in development, for both efficacy and safety, which should ultimately reduce overall costs/timelines and provide better dos-ing information. The rapid proliferation of adaptive designs and inconsistent use of terminology have created confusion about the similarities and, more importantly, the differences among the techniques. This half-day course will clarify the differences between adaptive dose-response trials and other types of adap-tive designs, review traditional fixed designs and adaptive dose-response designs, and provide information about developing a Bayesian adaptive dose-response trial. Real and simulated data examples will be used. Attendees should be in the second year of a graduate program and have basic knowledge of Bayesian meth-ods and exposure to drug development concepts.

FEES: M–$210 ($285), NM–$275 ($345), S–$125 ($200)

Longtime Member Reception

by invitation only

Monday, July 30, 6:30 to 7:30 p.m.The Grand America Hotel

Murano Garden SalonIf you joined the ASA 35 or more years ago,

the American Statistical Association would like to thank you for

your longtime support.

Please join us for a reception inyour honor.

Sponsored by the ASA Membership Retention and Recruitment Committee.


CE_15C 8:00 a.m.–12:00 p.m.Categorical Data AnalysisInstructor: Charles S. Davis

Categorical variables occur frequently in many types of research. The purpose of this course is to introduce, discuss, and provide examples of several approaches for analyzing data in which the response variable is categorical. The course will provide a reasonably comprehensive overview of the basic methods of most use to applied statisticians. It is not intended to be a state-of-the-art summary of research in the field. The topics to be discussed include methods for the analysis of two-way and stratified two-way contingency tables, logistic regression for binary and polytomous responses, weighted least squares analysis of categorical data, and loglinear mod-els. Examples using SAS software will be presented. Attendees should have general statistical education at the master’s level (including a mathematical statistics course at the level of Hogg, Craig, and McKean’s Introduction to Mathematical Statistics) and familiarity with regression and ANOVA mod-els for continuous response variables.

FEES: M–$210 ($285), NM–$275 ($345), S–$125 ($200)

CE_16C 8:30 a.m.–5:00 p.m.Multiple Comparisons and Multiple TestsInstructor: Peter H. Westfall

This short course will cover multiple comparisons and mul-tiple testing methods, from basic and state-of-the-practice to advanced and state-of-the-art. Topics include “family” choice, combined versus component tests, interval versus test-based inference, intersection-union versus union-intersection tests, false discovery rate versus familywise error rate, and Bayes/frequentist views. Models include standard ANOVA, regres-sion, and multivariate analysis, as well as more general mod-els, such as those used in survival analysis, GLIMs, mixed models, and nonparametrics. Current software implementa-tions based on recent research in JASA will be emphasized. Applications include clinical trials, agriculture, business, and genetics. Attendees should have knowledge of probability-based statistical inference through ANOVA, regression, and applied multivariate analysis.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_17C 8:30 a.m.–5:00 p.m.Analysis of Clinical Trials: Theory and ApplicationsCosponsor: Biopharmaceutical SectionInstructors: Christy Chuang-Stein, Alex Dmitrienko,and Geert Molenberghs

This course covers analysis of stratified data, multiple com-parisons and multiple endpoints, interim analysis and interim data monitoring, and analysis of incomplete data. It offers a well-balanced mix of theory and applications, presents practical advice from experts, and discusses regulatory con-siderations. The discussed statistical methods will be imple-mented using SAS software, and clinical trial examples will be used. The course is designed for statisticians working in the pharmaceutical or biotechnology industries and contract research organizations. It is equally beneficial to statisticians working in institutions that deliver health care and govern-ment branches that conduct health care–related research. This course was taught at JSM 2005 and 2006 and received the Excellence-in-CE Award in 2005. Attendees are required to have basic knowledge of clinical trials. Familiarity with drug development is desirable, but not necessary.

Recommended Textbook: Dmitrienko, A.; Molenberghs, G.; Chuang-Stein, C.; Offen W. (2005). Analysis of Clinical Trials Using SAS: a Practical Guide. SAS Publishing. ISBN: 9781590475041.FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_18C 8:30 a.m.–5:00 p.m.Temporal Alerting Algorithms for BiosurveillanceCosponsors: Section on Statistics in Defense and National Security, Section on Risk Analysis, and Section on Quality and ProductivityInstructors: Howard S. Burkom and David Banks

This course will present concepts and application issues of statistical alerting algorithms for syndromic surveillance. Methods for prospective monitoring of univariate and multivariate time series will be included. The public health context and selection of the input data streams will be discussed, along with the consequent logistical constraints. The necessary background for statistical process control and data forecasting methodologies will be



Monday, July 30Continuing Education


provided with explanations for how these traditional approaches are adapted for routine public health implementation. Emphasis will be on applications, with discussion of how to manage seasonal and day-of-week effects and other temporal correlation issues, as well as customary data acquisition problems. Methods for evaluating algorithm detection performance will be presented with the goal of optimizing sensitivity to disease outbreaks at false alarm rates acceptable to public health investigation capability.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_19C 8:30 a.m.–5:00 p.m.Practical Bayesian Clinical Trial DesignCosponsor: Section on Bayesian Statistical ScienceInstructor: Peter F. Th all

This course will cover practical Bayesian methods for clini-cal trial design and conduct. Attendees should have at least a master’s degree in statistics or equivalent experience and an understanding of elementary Bayesian concepts. The course will include numerous illustrations using actual clinical trials. Most examples will be drawn from oncology, although the methods are broadly applicable. Methods for eliciting and calibrating priors,

incorporating historical data, and using computer simulation to establish a design’s frequentist properties will be illustrated. The morning will be cover phase I and phase I/II designs, including dose-finding using the continual reassessment method and logis-tic regression models, accommodating multiple ordinal toxicities weighted by their clinical importance, finding optimal dose pairs of two agents used in combination, dose-finding based on effi-cacy-toxicity trade-offs, optimizing schedule of administration rather than dose, and jointly optimizing dose and schedule. The afternoon will cover single-arm and randomized phase II trials and hybrid designs that incorporate several methods. These will include a paradigm for monitoring multiple discrete outcomes, phase II designs based on event times, hierarchical Bayesian methods for trials with multiple disease subtypes, using regres-sion to account for patient heterogeneity, adaptive randomiza-tion, and optimizing multistage dynamic treatment strategies.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_20C 8:30 a.m.–5:00 p.m.Classifi cation and Regression TreesInstructor: Wei-Yin Loh

In a classification or regression tree model, the data space is split into several partitions and a simple statistical model is fitted to each partition. This course reviews the major algorithms, includ-ing C4.5, CART, CHAID, CRUISE, GUIDE, M5, and QUEST. Also covered are ensemble procedures, such as bagging, and various types of regression, including least squares, quantile, Poisson, logistic, and relative risk regression. The emphasis is on showing the strengths and weaknesses of the methods and their capabilities compared to non-tree methods. The methods are compared in terms of prediction accuracy, model interpretabil-ity, selection bias, and computational requirements. Examples will be drawn from business, economics, medicine, engineering, science, and sports. Relevant software will be discussed where appropriate. Attendees should be familiar with linear regression at the level of Weisberg’s Applied Linear Regression and dis-criminant analysis at the level of Johnson and Wichern’s Applied Multivariate Statistical Analysis.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_21C 1:00 p.m.–5:00 p.m.Meta-analysis: Statistical Methods for Combining the Results of Independent StudiesInstructor: Ingram Olkin

Meta-analysis enables researchers to synthesize the results of a number of independent studies designed to determine the effect of an experimental protocol, such as an intervention, so the combined weight of evidence can be considered and applied. In this course, I will provide a historical perspective of meta-analysis and discuss various types of bias and the effects of heterogeneity. Statistical methodology will include discussions of nonparametric and parametric models, effect sizes for proportions, fixed versus random effects, regression, and ANOVA models. New material on multivariate models also will be presented.

FEES: M–$210 ($285), NM–$275 ($345), S–$125 ($200)

REGISTER Onlinewww.amstat.org/meetings/

jsm/2007/onlinereg




Tuesday, July 31

CE_22C 8:00 a.m.–12:00 p.m.Harnessing Data Streams through Statistical ComputingCosponsor: Section on Statistical ComputingInstructors: Tamraparni Dasu and Simon Urbanek

Data streams are a predominant form of information today, arising in areas and applications ranging from telecommu-nications, meteorology, and rocketry to the monitoring and support of e-commerce sites. They pose unique analytical, statistical and computing challenges just beginning to be addressed. In this course, we will give an introduction and overview of the analysis and monitoring of data streams. We will give an overview of existing literature and applica-tions, highlighting opportunities for statistical research where appropriate. We will make extensive use of examples and real-life applications to elucidate the material and conclude with a discussion of open research problems.

FEES: M–$210 ($285), NM–$275 ($345), S–$125 ($200)

CE_23C 8:30 a.m.–5:00 p.m.Statistical Monitoring of Clinical Trials: a Unifi ed ApproachCosponsor: Biopharmaceutical SectionInstructor: Michael Proschan

This course will use the B-value approach to show how to monitor many types of trials, including those with continuous, dichotomous, or survival endpoints, with or without adjust-ment for covariates. This means the same boundaries can be used for different types of trials. Moreover, we will show that calculations performed under the alternative hypothesis depend on only the expected value of the z-score at the end of the trial. We will use this to show how to compute and inter-pret conditional and unconditional power, which are useful in deciding whether to stop a trial for futility. We will then cover different monitoring boundaries (including the flexible error spending function approach), inference following a group-sequential trial (p-values, estimation, and confidence inter-vals), Bayesian methods, and adaptive sample size methods.

We also will discuss what to do when the B-value paradigm is not applicable.

Recommended Textbook: Proschan, M.A.; Lan, K.K.G.; and Wittes, J.T. (2006). Statistical Monitoring of Clinical Trials: a Unified Approach. Springer. ISBN: 9780387300597.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_24C 8:30 a.m.–5:00 p.m.Dropout in Longitudinal Studies: Strategies for Bayesian Modeling and SensitivityCosponsor: Biometrics SectionInstructors: Michael J. Daniels and Joe Hogan

This course will provide a survey of modern model-based approaches to handling dropout in longitudinal studies and illustrate the use of newly developed methods for sensitivity analysis and incorporation of prior information. The emphasis will be on Bayesian approaches, but the models and methods discussed can be implemented in non-Bayesian settings. The course will begin with a brief review of models for longitudi-nal data and the basics of Bayesian inference. Included will be a quick primer on the WinBUGS software, used through-out the course to illustrate the concepts and models on real data examples. The second part of the course will focus on dropout. We will discuss formal classifications of the drop-out mechanism and describe different classes of models to adjust for biases caused by dropout. We also will discuss the importance of model specification and the logistics of model fitting. Models for both ignorable and nonignorable dropout will be covered. The final part of the course will focus on nonignorable dropout; we will describe and motivate prin-ciples that should guide assessment of sensitivity to missing data assumptions and appropriate use of prior information. Attendees should have working knowledge of generalized lin-ear models and statistical inference at the master’s level.

FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

Continuing Education


CE_25C 8:30 a.m.–5:00 p.m.Statistical GeneticsCosponsor: Biometrics SectionInstructors: Kenneth Lange, Janet Sinsheimer, and Eric Sobel

This short course will present an overview of statistical genet-ics with an emphasis on methods for detection of genetic loci for complex traits. The course will be balanced between theory and applications. After a brief but thorough refresher on the biological principles underlying statistical genetics, we will cover statistical models that underlie many pedi-gree-based gene mapping methods. We will then cover the statistical theory and implementation of methods for allele frequency estimation, estimation of ethnic admixture, trans-mission distortion and gene mapping, penetrance estimation using generalized linear models, variance component models for quantitative trait mapping, and variance component mod-els for inbred strains. Attendees should have familiarity with basic statistical modeling and likelihood theory.

Recommended Textbook: Lange, K. (2002). Mathematical and Statistical Methods for Genetic Analysis, 2nd edition. Springer. ISBN: 9780387953892.FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_26C 8:30 a.m.–5:00 p.m.Wavelets and Statistical ApplicationsCosponsor: Section on Bayesian Statistical ScienceInstructors: Marina Vanucci and Brani Vidakovic

Statistical wavelet modeling and computational research has, in this decade, become a burgeoning area in theoretical and applied statistics and is, in many cases, guiding the develop-ment of statistical methodologies in various interdisciplin-ary fields. This course, aimed at statisticians and scientific investigators interested in the practical use of wavelets for the analysis of data, will focus on the use of wavelet methods in statistics. It will start with a brief introduction to the wavelet theory, followed by an overview of wavelet-based statistical methods and applications. Topics will include smoothing of noisy signals, nonparametric estimation of functional data, and representation of stochastic processes. Emphasis will be given to Bayesian inferential procedures. Matlab software will be used, and complex mathematical details will be only partially covered.

Recommended Textbook: Vidakovic, B. (1999). Statistical Modeling of Wavelets. Wiley. ISBN: 9780471293651FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_27C 8:30 a.m.–5:00 p.m.Analysis of Censored DataInstructor: Danyu Lin

The purpose of this course is to review some of the key devel-opments of statistical theory and methods for analyzing cen-sored event-time data. We will provide a heuristic introduction to the counting-process martingale theory before using the tool to understand the properties of commonly used statistics, such as the Kaplan-Meier estimator, (weighted) log-rank tests, and Cox proportional hazards regression. We will address practi-cal issues in applying the Cox model to real studies, including variable selection, model checking, model misspecification, and robust inference. We also will review recent advances in the field, including analysis of multiple events data, informative drop-out, and joint modeling of repeated measures and event times. Relevant software will be described, and a number of clinical and epidemiologic studies will be provided for illustra-tion. This course is aimed at applied statisticians (particularly clinical trial statisticians) who wish to analyze their data with the best available methods. Basic knowledge in mathematical statistics and linear models is required. No prior knowledge of survival analysis is necessary.

Recommended Textbook: Kalbfleisch, J.D. and Prentice, R.L. (2002).The Statistical Analysis of Failure Time Data. FEES: M–$340 ($450), NM–$435 ($545), S–$200 ($325)

CE_28C 1:00 p.m.–5:00 p.m.Bootstrap Methods and Permutation Tests for Doing and Teaching StatisticsCosponsors: Section on Statistical Education and Section on Statistical ComputingInstructor: Tim Hesterberg

In this course, we will see how inaccurate normal-based methods are in the presence of even moderate skewness. The old rule of trusting the CLT if n>30 is just old. Bootstrapping and permutation tests (BPT) let us more easily do infer-ences for a wider variety of statistics (e.g. trimmed means, robust regression) for data collected in a variety of ways (e.g., stratification). BPT provide output we may graph in familiar ways (e.g., histograms) to help students and clients under-stand sampling variability, standard errors, p-values, and the Central Limit Theorem (CLT)—not just in the abstract, but for the dataset and statistic at hand. We will look at applica-tions from a variety of fields, including telecommunications, finance, and biopharm.

Recommended Textbooks: Hesterberg, T.; Monaghan, S.; and Moore, D.S. (2003). Bootstrap Methods and Permutation Tests. W.H. Freeman. ISBN: 0716757265.Hesterberg, T. (2004). Supplement to Bootstrap Methods and Permutation Tests. Insightful Corporation.FEES: M–$210 ($285), NM–$275 ($345), S–$125 ($200)


REGISTRATION FORM (each participant must complete and sign form)

____________________________________________________________________________________________________________Name____________________________________________________________________________________________________________Address

___________________________________________________________________________________________________________City, State/Province ZIP/Postal Code Phone

SEX: ❏ M ❏ F Age ______ EVENT: ❏ 5 K Race ❏ 2.5 K Fun Run/Walk T-SHIRT SIZE: ❏ S ❏ M ❏ L ❏ XL

THE FINE PRINT. I understand that running a road race is a potentially hazardous activity. I will not enter and run unless I am medically able and properly trained. I agree to abide by any decision of a race official relative to my ability to complete the run safely. I assume all risks associated with running in this event, including, but not limited to, falls; contact with other participants; and effects of weather, traffic, and course conditions. All such risks are known and appreciated by me. Having read this waiver, knowing these facts, and in consideration of your accepting my entry, I, for myself and anyone entitled to act on my behalf, waive and release the race directors, the race committee, and all sponsors from all claims of liabilities of any kind arising out of my participation in this event, even though such liability may arise as a result of negligence or carelessness on the part of the persons named in this waiver.

________________________________________________________________________________________________________Signature

_________________________________________________________________________________________________________Date Parent or guardian (if under 18)

The Caucus for Women in Statistics, in conjunction with the ASA, presents the 18th annual Gertrude Cox Scholarship Race at the Joint Statistical Meetings in Salt Lake City, Utah. All proceeds will benefit the Gertrude M. Cox Scholarship in Statistics.

The Race: There will be two races running concurrently—a competitive 5K race and a 2.5K fun run/ walk.

When: Tuesday, July 31, at 7:00 a.m.

Where: Location and logistical information will be posted at the Caucus table at the Salt Palace Convention Center.

How Much: The entry fee is $20.00.

Registration: Those interested in participating are encouraged to register early. You may register during JSM at the hospitality table for the Caucus for Women in Statistics at the Salt Palace Convention Center, near the registration area. All participants must sign a reg-istration form and waiver. T-shirts for all preregistered runners will be distributed at the race. If you have questions, please contact Karen Davis at [email protected].

Make check payable to The Gertrude Cox Scholarship Fund. Please return this form along with your check to

Karen Davis, Race Organizer, National Center for Health Statistics, 3311 Toledo Road, Room 3213, Hyattsville, MD 20782.

GERTRUDE COX SCHOLARSHIP RACEThe 18th Annual

Time Course Instructor(s) Title

8:00 a.m.–9:45 a.m. CE_29T Mikhail Golovnya Introduction to CART: Data Mining with Decision Trees

8:00 a.m.–9:45 a.m. CE_30T Angela Pitts/G. Gordon Brown

New Features for Clustered and Survey Data Analysis in SUDAAN® Release 9.0.3

8:00 a.m.–9:45 a.m. CE_31T Robert Cohen Modern Regression Analysis in SAS Software

8:00 a.m.–9:45 a.m. CE_32T Michael Borenstein/Hannah Rothstein

Power Analysis: a Simple and Effective Approach

8:00 a.m.–9:45 a.m. CE_33T Cyrus R. Mehta East® 5: a Comprehensive Package for Adaptive and Group Sequential Design, Interim Monitoring, and Simulation

10:00 a.m.–11:45 a.m. CE_34T Mikhail Golovnya Introduction to MARS: Predictive Modeling with Nonlinear Automated Regression Tools

10:00 a.m.–11:45 a.m. CE_35T Shawn Harahush From Software to Solutions in Statistics and Risk Analysis

10:00 a.m.–11:45 a.m. CE_36T Sharad Prabhu/José G. Ramírez

Design and Analysis of Split-Plot Experiments Using the SAS ADX Interface

10:00 a.m.–11:45 a.m. CE_37T Michael Borenstein/Hannah Rothstein

Meta-analysis: Concepts and Applications

10:00 a.m.–11:45 a.m. CE_38T Weicai Zhong Generalized Linear Modeling in SPSS

1:00 p.m.–2:45 p.m. CE_39T Mikhail Golovnya Advances in Data Mining: Jerome Friedman’s TreeNet/MART and Leo Breiman’s Random Forests

1:00 p.m.–2:45 p.m. CE_40T Colin (Lin) Chen Quantile Regression Using the SAS QUANTREG Procedure

FEE: $50 each


Computer Technology Workshops at a glance

Computer Technology WorkshopsWednesday, August 1


CE_29T 8:00 a.m.–9:45 a.m.Introduction to CART: Data Mining with Decision TreesInstructor: Mikhail Golovnya

This course, intended for the applied statistician wanting to understand and apply the CART methodology for tree-struc-tured nonparametric data analysis, will emphasize on practi-cal data analysis involving classification. All concepts will be illustrated using real-world examples. The course will begin with an intuitive introduction to tree-structured analysis. Working through examples, we will review how to read CART output and set up basic analysis. This session will include performance evaluation of CART trees and cover ways to search for possible improvements of the results. Once a basic working knowledge of CART has been mastered, we will focus on critical details essential for advanced CART applica-tions, including choice of splitting criteria, choosing the best split, using prior probabilities to shape results, refining results with differential misclassification costs, the meaning of cross validation, tree growing, and tree pruning. The course will conclude with discussion of the comparative performance of CART versus other computer-intensive methods, such as arti-ficial neural networks and statistician-generated parametric models. FEE: $50

CE_30T 8:00 a.m.–9:45 a.m.New Features for Clustered and Survey Data Analysis in SUDAAN® Release 9.0.3Instructors: Angela Pitts and G. Gordon Brown

This workshop will highlight 10 new features in SUDAAN Release 9.0.3 available to researchers analyzing cluster-cor-related or complex survey data. These features include CMH Test of Trends; addition of new test statistics, including the Rao-Scott test; small proportion confidence interval esti-mation; introduction of a weighted kappa; chi-squared test to known proportions; updated memory manager; revised PRINT capabilities; logrank test in KAPMEIER; percentile correction in PROC DESCRIPT; and INCLUDE option in every procedure. The workshop will include a brief review of statistical problems encountered in survey data, plus a brief introduction to SUDAAN syntax. Attendees are not required to be SUDAAN users, but should have a good knowledge of statistical issues present in correlated data and surveys and be familiar with commonly used statistical methods and categorical data analysis. The new SUDAAN features will be demonstrated on complex survey data. We will demonstrate proper implementation of SUDAAN, provide interpretation of the output, and discuss statistical issues related to the data. The datasets, SUDAAN code used in the presentation, and a 30-day trial version of SUDAAN Release 9.0.3 will be pro-vided to attendees. FEE: $50

CE_31T 8:00 a.m.–9:45 a.m.Modern Regression Analysis in SAS SoftwareInstructor: Robert Cohen

This workshop is intended for a broad audience of statisti-cians and data analysts who are interested in modern regres-

sion methods. I will describe these methods and SAS tools for fitting robust local regression models with the LOESS proce-dure, robust parametric models with the ROBUSTREG proce-dure, quantile regression models with the new QUANTREG procedure, mixed model smoothing with the new GLIMMIX procedure, and LASSO/LAR regression models with the new GLMSELECT procedure. These tools are illustrated with sev-eral examples. Attendees should have a basic understanding of regression theory. FEE: $50

CE_32T 8:00 a.m.–9:45 a.m.Power Analysis: a Simple and Effective ApproachInstructors: Michael Borenstein and Hannah Rothstein

This workshop offers an introduction to power analysis and shows how to use it simply and effectively to plan studies and write grant applications. Power analysis is the art of finding and justifying a sample size for a planned study. Power is determined by such factors as the magnitude of the treatment effect, the sample size, alpha, and (for survival studies) the study duration. The goal of the power analysis is to balance these as a series of “what ifs,” done most effectively with graphs that allow the researcher to grasp (and communicate) a range of options in a single picture, and then find the one that strikes the optimal balance of feasible sample size, reasonable assumptions, and acceptable power. We will show how to do this using Power And Precision. We will use examples from means, proportions, and survival analysis. This workshop is recommended for people new to power analysis, frustrated by power analysis, and who need to perform power analysis for survival studies. FEE: $50

CE_33T 8:00 a.m.–9:45 a.m.East® 5: a Comprehensive Package for Adaptive and Group Sequential Design, Interim Monitoring, and SimulationInstructor: Cyrus R. Mehta

We will release East® 5, a major upgrade of the East software package for design, interim monitoring, and simulation of adaptive and group sequential clinical trials. New analyti-cal and simulation capabilities are provided for the survival setting that can accommodate fixed and variable follow-up, nonuniform accrual, varying hazard rates, and drop-outs. The software will support both group sequential designs, where early stopping is the goal, and adaptive designs, where sample size re-estimation is the goal. For the sample size re-estima-tion problem, we will demonstrate how East can compute confidence intervals and point estimates following an adaptive design. Finally, we will demonstrate a new East module for adaptive dose-response modeling. FEE: $50

CE_34T 10:00 a.m.–11:45 a.m.Introduction to MARS: Predictive Modeling with Nonlinear Automated Regression ToolsInstructor: Mikhail Golovnya

This workshop will introduce the main concepts behind Jerome Friedman’s MARS, a modern regression tool that can help

Computer Technology Workshops


for people who need to perform or interpret meta-analyses in their work. Attendees should have some familiarity with meta-analysis, but the course will cover the basics before moving to more advanced topics. FEE: $50

CE_38T 10:00 a.m.–11:45 a.m.Generalized Linear Modeling in SPSSInstructor: Weicai Zhong

GENLIN covers a variety of exponential distributions to analyze different data—including normal, gamma, inverse Gaussian, Poisson, negative binomial, and binomial—and many types of link functions—including identity, complemen-tary log-log, log, log complement, logit, negative binomial, negative log-log, odds power, probit, and power. In this work-shop, we will introduce model details and show how to choose and fit a generalized linear model using examples of data in applied research. We will demonstrate assessing the fit of a model, comparing it against competing models, interpreting the parameters, and performing follow-up analysis, such as estimated marginal means or scoring. Examples will illustrate the use of GENLIN. Attendees are expected to have basic knowledge of statistical inference. Familiarity with classical linear modeling is desirable, but not required. FEE: $50

CE_39T 1:00 p.m.–2:45 p.m.Advances in Data Mining: Jerome Friedman’s TreeNet/MART and Leo Breiman’s Random ForestsInstructor: Mikhail Golovnya

This workshop will present Leo Breiman’s Random Forests and Jerome Friedman’s TreeNet™/MART (also known as TreeNet Stochastic Gradient Boosting). Random Forests and MART/TreeNet are new advances to classification and regression tree software, which enable the modeler to construct predictive models of extraordinary accuracy. Random Forest is a tree-based procedure that makes use of bootstrapping and random feature generation. In TreeNet, classification and regression models are built gradually through a potentially large collection of small trees, each of which improves on its predecessors through an error-correcting strategy. I will show how the software is used to solve real-world data mining problems, cover theory and discuss what is novel in the software, cover implementation, compare the two methodologies, and show where the software fits in terms of other data mining software. FEE: $50

CE_40T 1:00 p.m.–2:45 p.m.Quantile Regression Using the SAS QUANTREG ProcedureInstructor: Colin (Lin) Chen

This workshop will introduce the SAS QUANTREG pro-cedure, which computes conditional quantile functions and conducts statistical inference on regression parameters. Participants will learn to explore the heterogeneity of both cross-sectional and longitudinal data and interpret quantile effects and quantile processes. Basic and advanced features of the procedure will be presented with examples, including the construction of growth charts for medical measurements. New features, including quantile regression splines, also will be demonstrated. FEE: $50

analysts quickly develop superior predictive models. MARS is a nonlinear automated regression tool that can trace complex pat-terns in the data. It automates the model specification search, including variable selection, variable transformation, interac-tion detection, missing value handling, and model validation. Conventional regression models typically fit straight lines to data. Although this usually oversimplifies the data structure, the approximation is sometimes good enough for practical pur-poses. However, in the frequent situations in which a straight line is inappropriate, an expert modeler must search tediously for transformations to find the right curve. MARS approaches model construction more flexibly, allowing for bends, thresh-olds, and other departures from straight lines from the begin-ning. Attendees will be presented with the key benefits over conventional regression tools and over a modelers’ tedious search for transformations to find the right curve. FEE: $50

CE_35T 10:00 a.m.–11:45 a.m.From Software to Solutions in Statistics and Risk AnalysisInstructor: Shawn Harahush

The world of business and education has become more com-plex with the decision of what software a business will use to successfully manage their incoming data. @RISK integrates into Microsoft Excel to provide a powerful Monte Carlo simu-lation engine for the ease-of-use environment. NeuralTools adds sophisticated neural networks analysis to Excel, and StatTools also integrates with Excel. FEE: $50

CE_36T 10:00 a.m.–11:45 a.m.Design and Analysis of Split-Plot Experiments Using the SAS ADX InterfaceInstructors: Sharad Prabhu and José G. Ramírez

The SAS ADX Interface is a point-and-click solution for statisticians, engineers, scientists, and other researchers who design, analyze, and interpret experiments to improve indus-trial processes and products. This workshop will introduce the ADX Interface, focusing on the design and analysis of split-plot experiments. We will review the basic concepts of split-plot designs and explain how to use the ADX Interface to construct and analyze various types of fractional-facto-rial split-plot designs. Examples will demonstrate the many interactive and graphical features of the ADX Interface, which requires no knowledge of SAS programming. FEE: $50

CE_37T 10:00 a.m.–11:45 a.m.Meta-analysis: Concepts and ApplicationsInstructors: Michael Borenstein and Hannah Rothstein

We will explain the concept of meta-analysis and discuss com-mon criticisms, such as “apples and oranges,” and conflicts between meta-analyses and clinical trials. We’ll explain how to compute treatment effects, synthesize data using various computational models, use ANOVA and meta-regression, create forest plots, and address the potential impact of publica-tion bias. We will show how to accomplish these tasks using Comprehensive Meta Analysis Version 2 (Borenstein, Hedges, Higgins, Rothstein), a new program developed with funding from the National Institutes of Health. The course is intended

Seeking a CAREER in

STATISTICS? Salt Lake City, UTJuly 29–August 1

What can the CAREER PLACEMENT SERVICE do for YOU?

Are you nearing graduation and wondering about entry-level jobs?Are you an experienced statistics professional interested in career information?

Register for the JSM Career Placement Service!

Career Placement Service BENEFITS

Each year, hundreds of companies, universities, recruiters, and government agencies search for applicants using the JSM Career Placement Service. Th e JSM Career Placement Service provides the best opportunity for qualifi ed applicants to meet employers, establish valuable contacts, and learn about organizations employing statisticians.

APPLICANT READING AREA—for applicants to review complete job descriptions and contact information for all registered employers.

VISIBILITY TO EMPLOYERS—applicants who register by July 12, 2007, will have their information and résumés included in the advance applicant access database, available to employers prior to the meeting. Employers often contact applicants in the database prior to JSM to schedule interviews.

COMPUTERIZED MESSAGE CENTER—allows applicants and employers to communicate throughout the meeting.

ONLINE ACCESS TO JOB POSTINGS—this year, included with ALL Career Placement Service registrations.

www.amstat.org/meetings/jsm/2007/placementOrganizations Represented at Recent JSM Career Placement Services

Capital One • FDA • Genentech • PPD • Stanford UniversityGE Consumer Finance • Pacifi c Northwest National Lab • Eli Lilly

Open to AllFirst-Timers(Dinner groups will form after the reception.)

You are invited to the JSM

First-Time Attendeeorientation and receptionSalt Palace Convention Center, Ballrooms A-BSunday, July 29, 6:00 p.m.–7:30 p.m.

This reception is sponsored by: ASA, ENAR, IMS, SSC, WNAR, The Caucus for Women in Statistics

AGENDA• Introduction: Tena Katsaounis, President, The Caucus for Women in Statistics

• Good Advice That I Ignored During My First JSM: Monnie McGee, Southern Methodist University

• Reception (light hors d’oeuvres to be served)

Learn more about how to get the most out of your fi rst JSM experience, meet new people, and network.



ASA Council of ChaptersOrganizer: V. A. Samaranayake, University of Missouri-Rolla

ML01 Reaching Out to the K–12 CommunityJerry Moreno, John Carroll UniversityOutreach to our schools is a natural and important activity for ASA Chapters. There is more and more opportunity and need for statisticians to be a viable resource for teachers and school districts as statistics continues to become an integral part of school cur-ricula. This roundtable will share ideas and best practices, how to get started, how to continue, and where to get funding. Activities to discuss will include science fair judging, data analysis workshops, project and poster competitions, career days, classroom visitations, school projects, adopt-a-school programs, and contributing to the Statistics Teacher Network. For those of you who have not been involved but want to, come and learn. For those who have been involved, come and share! Statisticians and teachers together can, and must, make a difference!

Section on Statistical EducationOrganizer: Jacqueline Miller, Ohio State University

ML02 Successful Statistics Class ProjectsDavid Zeitler, Grand Valley State UniversityJoin us to discuss experiences and ideas for the design, imple-mentation, and evaluation of projects in statistics classes. These projects provide the opportunity for higher-level learning in ways that cannot be duplicated with homework, quizzes, or exams as students take those first tentative steps beyond manipulating data toward real understanding of information. Both instructor and student viewpoints are welcome as we explore project ideas, team setup and building, project organization and tracking, and methods for evaluation.

ROUNDTABLES

Monday, July 30Time: 7:00 a.m.–8:15 a.m.

Menu: Freshly baked pastries, muffins, and breakfast breads served with butter and jam; orange, apple, and cranberry juices; regular and decaffeinated coffee; and hot tea

Fee: $12 each (includes continental breakfast)

Roundtables with Coffee

Section on Statistics and the EnvironmentOrganizer: Andrew B. Lawson, University of South Carolina

ML03 Hierarchical Spatial Models Bridging Ecology and Public Health Lance Waller, Emory UniversityDisease ecology focuses on environmental and ecological impacts on the emergence and spread of disease and reflects an ongoing inter-disciplinary interaction between biologists, ecologists, physicians, veterinarians, and public health scientists. Such studies quantify patterns in data from genetic sequencing of pathogens, host behav-iors and interactions, and landscape habitat features. This requires flexible statistical methods that incorporate the full range of data, modeling at a variety of scales, and allowing variable data quality and accuracy. Hierarchical models provide a framework for bridging dynamic systems with multiple levels of data. Established successes appear in the fields of climate modeling and the ecology of invasive species. The goal of this roundtable is to extend such approaches to disease ecology.

ML04 What’s the Future for Point Process Modeling in Ecology?Philip Dixon, Iowa State UniversityThe analysis of spatial point patterns has a long history in ecol-ogy. Over time, ecological questions and statistical methods have changed. The three-fold classification into random, clustered, or seg-regated patterns has been replaced by multiscale summaries using Ripley’s K function or pair correlation functions. This roundtable will gather folks to discuss what’s next. What questions do ecolo-gists want to answer that can’t be answered with current methods? What statistical methods might provide better answers to current questions?

Section on Statistics in EpidemiologyOrganizer: William E. Barlow, Cancer Research and Biostatistics

ML05 Building and Using Disease Prediction Models in the Real WorldHeejung Bang, Cornell UniversityBuilding risk score or prediction models is an area of mathemati-cal/statistical modeling that can have a huge impact on patient care. Accuracy and user-friendliness are two required criteria in the development of any prediction model to be not only accepted by clinicians and policymakers, but also commonly used by the general public. We will discuss popular statistical methodologies and the risk models utilized in a variety of real settings. The larger


question is how we get our ‘good’ models into common practice. To illustrate this, I will present models for diabetes and kidney disease. Other participants may want to discuss their prediction models or schemes and how they are being used in practice.

Section on Statistics in SportsOrganizer: Michael J. Schell, Moffi tt Cancer Center

ML06 Moneyball and the NFL: Can It Work? Keith Schleicher, Capital OneMichael Lewis’ best-seller, Moneyball, showed how one baseball team used statistical analysis to gain competitive advantage. Could the same hold true for professional football? Can an NFL team help itself by using statistical analysis to inform personnel decisions, game preparation, and in-game decisionmaking? Possible questions to consider include the following: Can a college quarterback’s per-formance be normalized for the game situations in which he played and the caliber of the opponent? How good is the NFL QB rating at comparing the performance of quarterbacks? Can statistics inform a coach’s decision to punt or go for it on fourth down?

Section on Survey Research MethodsOrganizer: David A. Marker, Westat

ML07 Web Panels: The Future of Survey Research? Karol Krotki, RTI InternationalIn light of current problems with traditional telephone surveys, do web surveys represent a viable option? Even if the sample is not based on a probability design?

Section on Teaching Statistics in the Health SciencesOrganizer: Jodi Lapidus, Oregon Health & Science University

ML08 Teaching Community Collaborators To Understand Health Research Methods and ResultsKatrina Ramsey, Northwest Portland Area Indian Health BoardMany population-based studies conducted by investigators at health research agencies and academic centers involve collabora-tion with community-based partners. A widely used framework in tribal health projects is Community Based Participatory Research (CPBR), which involves community members in “every facet of the research process.” If community members are to have substantial input into research design, analysis, and interpreta-tion, they need some understanding of these concepts. However, lack of formal statistics training, as well as many other factors, may make it difficult for some of our collaborators to understand, and ultimately use, the information gained from studies conduct-ed in their communities. The goal of this roundtable is to discuss successful (and possibly unsuccessful) methods for teaching and communicating with our community-based research partners.

Sunday, July 298:00 p.m.–10:30 p.m.Salt Palace Convention Center, Ballrooms C-J

Opening Mixer


Biopharmaceutical SectionOrganizer: Kalyan Ghosh, Vislation Inc.

ML10 Innovative Design and Analysis of FDA Medical Device SubmissionsGary Kamer, U.S. Food and Drug AdministrationThis discussion will emphasize the acceptability of recently devel-oped statistical methodologies to establish the safety and effective-ness of new medical devices seeking to be marketed in the United States. It is anticipated that there will be a broad range of meth-odologies discussed, along with their strengths, weaknesses, and alternatives. Concentration will be on frequentist procedures, but Bayesian issues also may be addressed.

ML11 Blocks, Strata, and Covariates: What’s in a Name?Veronica Taylor, U.S. Food and Drug AdministrationBlocks, strata, and covariates may be used to reduce variance to provide a better test for treatment effects of interest. Sometimes the

terms are used interchangeably. However, each concept has different processes and assumptions attached. We will discuss the underlying assumptions; uses in experimental design; and possible analyses when blocks, strata, or covariates are used.

ML12 The Use of Meta-analysisin Drug DevelopmentTsushung Hua, Novartis PharmaceuticalsMeta-analysis (MA) is a statistical method to obtain an overall drug (treatment) effect or results from independent, but related, trials. Lately, medical journals have published more papers from meta-analyses to show the efficacy and safety of a drug or class of drugs. In this roundtable, we will discuss the method and application of MA in drug development.

ML13 Evaluating Probability of Success for Internal Decisionmaking in Early Drug Development Narinder Nangia, Abbott LaboratoriesThere is a need to look beyond p-values in drawing meaningful

Section on Statistics in Sports Organizer: Michael J. Schell, Moffi tt Cancer Center

When commentators and the sporting public talk about Tiger Woods, they inevitably say he has a tremendous will to win and is mentally better than everyone else. Sports are notorious for attach-ing “reasons” to randomness—there has to be a reason he wins so darn much. The sports world also loves “winners.” Is Tiger Woods a winner, or is he so much better than everyone else that he just wins a lot? In this talk, I use a Bayesian hierarchical model to address how good Tiger Woods is—and why he wins so much. If time permits, I also will discuss what elements of his game make him so good; is it his individual measurable attributes, or his intangibles?

Speaker with Lunch

Monday, July 30Time: 12:30 p.m.–1:50 p.m. Regular–Salad of baby field greens, asiago-crusted

chicken breast topped with oven-dried tomato sauce, creamy polenta, and cappuccino chocolate cream layer cakeVegetarian–Salad of baby field greens; udon noodles and garden vegetables served in a black bean garlic sauté, topped with fire-roasted portabella mushrooms, and garnished with fine bean threads; and fresh fruit cupChef’s choice of kosher and heart healthy menus also available

Fee: $40 each (includes meal)

Speaker and Roundtables with Lunch

Scott M. Berry earned his PhD from Carnegie Mellon and his BS from the University of Minnesota. He current-ly consults and has been involved in adaptive Bayesian clinical trial design for pharmaceutical and medical device companies. For eight years, he wrote a sports column for CHANCE, and he has published in a range of sports-related publications, including ESPN the Magazine.

ML09 Is Tiger a Winner, or Is He Just Better Than Everyone?Scott Berry, Berry Consultants

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inference from the analysis of phase I–II (learning stage) clinical trials data. This discussion will be on using the Bayesian approach to exploit totality of accumulated data/knowledge in a formal way for internal decisionmaking in early drug development. Examples from inflammation and oncology therapeutic areas will be considered for evaluation of probability of success for drug candidates in meeting the target product profile.

Business and Economics Statistics SectionOrganizer: Clifford M. Hurvich, New York University, Stern School of Business

ML14 Statistics Teaching: Bayesian, Frequentist, UnitedEmanuel Parzen, Texas A&M UniversityAll statisticians have problems understanding the distinction between confidence intervals and credible intervals (which I call statistical inference without priors and with priors, rather than frequentist and Bayesian inference). In introductory statistics edu-cation, the question is how to teach Bayesian prior methods while teaching with equal emphasis on frequentist nonprior methods. We propose that the practice of statistical inference requires jug-gling several distributions simultaneously and a village of quantile functions of distributions. One important consequence of parallel reasoning between posterior quantiles and confidence quantiles (endpoints of confidence intervals) is that they provide for hypoth-esis testing of both Bayesian and frequentist solutions. We recom-mend using and comparing both.

Section on Bayesian Statistical ScienceOrganizer: David A. van Dyk, University of California, Irvine

ML15 Dealing with Review Effi ciency: a Practical Bayesian Approach Xiao-Li Meng, Harvard UniversityThe slow manuscript review process has frustrated generations of statisticians, Bayesian or not. Many have put in tremendous effort to improve review efficiency, but more collective effort is needed to fundamentally shift our slow review culture. Some believe Bayesians have solutions to every problem, especially in improving efficiency. A Bayesianly justifiable approach was recently implemented by Statistica Sinica, with a result that appears to support that belief. The median for Statistica Sinica’s first review period (from the date of submission to first editorial decision sent) is now about five weeks, with 95% percentile about four months and 100% percentile about six months. Undoubtedly, this right tail is still too long, so please join me in brainstorming ways to further improve, especially if you believe you can do better than Bayesians.

Section on Government StatisticsOrganizer: Michael E. Davern, University of Minnesota

ML16 Design and Use of the IPUMS-International Data Series Matthew Sobek, University of MinnesotaThe Integrated Public Use Microdata Series (IPUMS) project is compiling the world’s largest public-use census database. The data system currently includes 63 census samples from 20 countries, containing the individual-level records of 185 million

persons. Samples from another 25 countries will be added over the next three years. The project harmonizes the data and docu-mentation across countries, and the web system produces data extracts that users download for analysis—all free of charge. This roundtable will discuss the design of the IPUMS, including key decisions of the research team and constraints imposed by inter-national statistical offices. We also will discuss the strengths and limitations of the data and directions for future development.

Section on Health Policy StatisticsOrganizer: Anirban Basu, University of Chicago

ML17 Estimation of Causal Effects in Health Services and Outcome Research Using Observational Data Lirong Zhao, University of MarylandSample selection bias is one of the major concerns in the estima-tion of causal effects using observational data in health services and outcome research when experimental designs are not fea-sible. Statisticians, epidemiologists, and econometricians have proposed many methods to adjust this bias over past decades. Propensity score and instrumental variable are two of the major methods that reduce the observable and unobservable biases, respectively. In this roundtable discussion, you will have the chance to share experiences of applications of these two methods in health policy statistics.

Section on Physical and Engineering SciencesOrganizer: Randall D. Tobias, SAS Institute Inc.

ML18 Sensor-Based Field Reliability Data Analysis: Opportunities and Challenges Necip Doganaksoy, General ElectricThe advances in sensor technologies have enabled manufacturers to track their products remotely and gather useful information to assess their health. The resulting data provides significant oppor-tunities, as well as challenges, to statisticians in automated moni-toring to identify impending failures. This is in sharp contrast to the recent past, when field reliability data were mainly comprised of after-the-fact failure information. Owing to large size and high dimension of sensor-based data, data mining and multivariate sta-tistical methods are particularly well-suited to tackle the technical challenges. In this roundtable, I will share my experiences from recent projects involving analysis and modeling of sensor data gathered from field units. Participants are encouraged to bring their examples to stimulate a useful exchange.

ML19 Non-Negative Matrix Factorization in StatisticsS. Stanley Young, National Institute of Statistical SciencesMatrix factorization, singular value decomposition, is the under-pinning of most linear statistical methods. Non-negative matrix factorization, NMF, takes into account that, in many cases, two-way data tables contain only non-negative numbers. NMF is being used in analytical chemistry, image processing, text clas-sification, blind signal separation, etc., but NMF is not widely considered in the statistics literature. There appears to be a wide scope for research on the use of NMF for statistical problems. The goal of this roundtable is to briefly present aspects of NMF and hear what is going on in this area. Participants are encour-aged to be ready to discuss their possible applications of NMF and/or analytic alternatives they have tried.


Section on Quality and ProductivityOrganizer: James D. Williams, GE Global Research

ML20 Exposing Students to Six Sigma as Part of Their University Training,Angie Patterson, GE Global ResearchUniversity students can benefit greatly from exposure to Six Sigma. Statistics majors (graduate and undergraduate) will gain nonstatis-tical skills (leadership, teamwork, structured problemsolving) that are not emphasized in their core coursework. Majors from other disciplines will be better motivated to learn statistical methodol-ogy when taught in an applied problemsolving framework. The discussion leader will share her experience in developing and teaching a master’s-level course in the Virginia Tech Department of Statistics (course overview, project selection, and student feed-back), as well as share teaching models at other universities. This roundtable discussion will benefit those interested in developing a course for their university and those wishing to network and share best practices from their experience.

Section on Risk AnalysisOrganizer: Susan Simmons, The University of North Carolina at Wilmington

ML21 Harnessing the Power of Information in Quantitative Risk Assessment Walter W. Piegorsch, University of ArizonaA broad discussion will be held on how modern information resources and technologies can be brought to bear on problems in quantitative risk analysis. Possible topics of pertinence will include potency estimation for dose-response data, excess risk estimation, benchmark analysis and benchmark dose estimation, large-data-base mining, uncertainty analysis, and sensitivity analysis. The discussion will remain as flexible as possible to include the many, wide-ranging aspects of modern quantitative risk assessment.

Section on Statistical ConsultingOrganizer: James Grady, University Texas Medical Branch

ML22 Right Answer, Wrong Question: Characterization and Reduction of the Risk of Type III Error in Statistical ApplicationsJohn L. Eltinge, Bureau of Labor Statistics2007 marks the 50th anniversary of the publication of an article by A. W. Kimball on Type III error, defined as “the error commit-ted by giving the right answer to the wrong problem.” This open roundtable will explore practical approaches to Type III error, with special emphasis on four questions: What do we mean by “wrong problem?” What are some especially notable examples of Type III error that the roundtable participants have encoun-tered in their consulting work? In light of the abovementioned examples, what systematic approaches can statisticians take to identify potential sources of Type III error, to detect these errors quickly when they occur, and to limit the impact of these errors? What practical implications do these systematic approaches have for the training and management of statistical consultants?


ML23 Spanning the Globe: Using Data To Introduce Students to the Rest of the WorldRobert Carver, Stonehill CollegeIn the introductory statistics course, we have the opportunity to expand the world view of our students. The simple idea is that there are numerous good international sources of data accessible online, and there are still precious few non-USA examples in most textbooks. At this roundtable, participants will swap sites, find out about easy and not-so-easy interfaces, and compare notes about the effective use of such data in the classroom and assignments.

ML24 TA Training for Introductory Statistics CoursesJessica Utts, University of CaliforniaThe statistics education community has made great progress in providing resources and advice for teaching introductory statistics. However, one major component of most introductory courses that has not received attention is the training of teaching assistants. At this luncheon, we will share information about what is done at our institutions and discuss what we can do better.

ML25 Learning To Teach Statistics: Challenges and Suggestions Candace Berrett, Ohio State UniversityAs students in statistics, most of us are expected to teach in some fashion, but we all begin with various backgrounds in teaching and in our knowledge of statistics, making a cookie cutter train-ing program difficult. At this roundtable, we will discuss various TA training strategies, what training you received (if any), the pros and cons of your training, and other preparation that would have been beneficial. Come and enjoy lunch with the company of other TAs, find out what others are doing to prepare to teach, and get ideas to improve your teaching.

Section on Statistical GraphicsOrganizer: David R. Hunter, The Pennsylvania State University

ML26 Graphical Data Mining of Network DataGeorge Michailidis, University of MichiganNetwork data have become ubiquitous in many scientific fields. They are capable of representing relationships between various entities, such as people in social or epidemiological contact net-works, machines in computer and communications networks, genes and proteins in biological networks, etc. They also pose various challenges due to their topological structure and large scale. Visualization is essential for exploring and analyzing such data. We will discuss techniques based on efficient graph-draw-ing algorithms for visualizing such data and for discovering inter-esting patterns and trends. They will be illustrated on a number of real-world examples from diverse fields.


objective of this roundtable is to discuss a set of statistical issues that, while not unique to gerontologic research, constitutes a distinctive ensemble worthy of deliberate and systematic atten-tion (i.e., design of multicomponent intervention trials, regres-sion modeling with missing data, evaluation of clinical tradeoffs, analysis of complex longitudinal datasets, and integration of qualitative studies with quantitative analyses). The roundtable will include a discussion of this year’s invited session devoted to gerontologic biostatistics and planning for future activities for statisticians interested in this topic.


ML29 What Happened in Florida-13’s Election Last Year? What Can We Do To Improve Electoral Integrity?Arlene Ash, Boston UniversityThe statistical evidence that poor electronic ballot design altered the outcome of the election for U.S. House of Representatives in Florida’s 13th Congressional district last year is compel-ling. The problem (that the screen needed to be scrolled to see how to vote in this race) led to >15,000 undervotes in the one county that favored the candidate who apparently lost by < 400 votes; voters in other counties faced a screen with no scrolling. Although this problem could have occurred innocently, ballot designers will likely continue to make such errors, innocently or not. We will discuss evidence from this election, reasons for the persistent failure to eliminate errors in U.S. elections (no CQI), the disconnect between statistical knowledge and political/judi-cial realities, and potential roles for statisticians (and the ASA) in helping to improve electoral processes and outcomes.

Social Statistics SectionOrganizer: Jana L. Asher, American Association for the Advancement of Science

ML30 Linking Survey Data and Administrative Data for Policy Research Michael Davern, University of MinnesotaLinked survey and administrative data files have great potential for policy research, as they can mitigate known problems with the survey data. By linking the survey data with administrative data, two major limitations are overcome. Survey data contain a significant amount of measurement error, especially when it comes to measuring public program enrollment. Administrative data do not include data on those eligible, but not enrolled, in the program or those who would potentially be eligible if the program rules changed. By linking the files, the eligible, but unenrolled, information can be provided by the survey data, and the program enrollment data can be provided by the administra-tive data (correcting the survey measurement error). This work is crucial for program simulation modeling used to score federal legislation and evaluate public programs.

Section on Statistics in Defense and National SecurityOrganizer: David J. Marchette, Naval Surface Warfare Center

ML27 Increasing Understanding of the Need for Statistics in Defense and Security Alyson G. Wilson, Los Alamos National LaboratoryIn 2006, the ASA president’s Task Force on Statistics in Defense and Security was charged to “provide advice and a plan on how the statistical community can better serve the needs of the nation in the areas of national defense and security and identify ways in which those communities can have greater access to statistical expertise and the statistical community can learn about areas of concern in defense and security.” In this roundtable, the task force chair (Alyson Wilson) and a member (Wendy Martinez) will discuss its recommendations and ask the following four ques-tions: Who are the main players in defense and security at the policy, funding, and application levels? What are the important problems that need statistics? How do we communicate statistics to the stakeholders? What are the lessons learned from previous attempts to do this?


ML28 Gerontologic Biostatistics and the Challenges of Conducting Biomedical Research with Older PopulationsPeter H. Van Ness, Yale UniversityMultifactorial etiologies of geriatric health syndromes and mul-tiple morbidities of older patients present challenges for design-ing and analyzing research studies in which they participate. The

REGISTER Onlinewww.amstat.org/meetings/

jsm/2007/onlinereg



TL03 Coordinating the Large Undergraduate CourseRoger Woodard, North Carolina State UniversityThis roundtable will address coordination of large undergradu-ate courses. Discussion will concentrate on practical solutions to administrative problems and improving student learning. Issues addressed will include working with large numbers of TAs, administering exams to large numbers of students, and handling general administrative tasks.


TL04 Network VisualizationDeborah Swayne, AT&T Labs – ResearchThe group will discuss the exploration of network data, by which we mean data that includes a mathematical graph—a set of verti-ces connected by edges. A key starting point is graph layout. We will discuss attributes of a good graph layout, useful web sites, and publicly available layout software. We also will discuss interaction with such graphs and look at a variety of interesting pictures.

Section on Statistics and MarketingOrganizer: Stan Lipovetsky, GfK Custom Research, Inc.

TL05 Statistics in Humor and Art Shon Magnan, GfK Custom Research North AmericaAt first blush, statistics do not seem to have much in common with humor and the arts. However, there are several examples from art, poetry, literature, and film where statistics are used as a theme. Many of us in our everyday work lives use humor to impart difficult statistical concepts to clients in ways they can understand. Join us in discussing how humor, the arts, and sta-tistics intersect. Bring your favorite statistical pictures, poems, web sites, etc.


TL06 The Transition from Graduate Schoolto a Career in Statistics Edward English, NORC at the University of ChicagoThe purpose of this roundtable is to discuss common issues and situations that arise for statisticians and related profession-

ASA Council of ChaptersOrganizer: V. A. Samaranayake, University of Missouri-Rolla

TL01 AP Statistics and Local Chapters of the ASA Dongseok Choi, Oregon Health & Science UniversityThe Advanced Placement (AP) program offers courses including statistics. Each AP course has a corresponding exam adminis-tered in May. Most colleges and universities in the United States have an AP policy granting incoming students credit, placement, or both on the basis of their AP exam grades. The AP statistics standard curriculum is equivalent to a noncalculus, one-semes-ter introductory college course in statistics. The Oregon Chapter of the ASA partnered with a few AP statistics teachers to identify common challenges and needs (e.g., shortage of properly trained teachers, lack of real-world examples, wishing for opportunities for interaction between teachers and professional statisticians, and class visits by statisticians). In this session, we will discuss how ASA Chapters can be resources for teachers and students in AP statistics and share our experiences.

Section on Health Policy Statistics Organizer: Anirban Basu, The University of Chicago

TL02 Approaches to Measuring Differences in Health That Are Unaffected by the Prevalence of an Outcome James P. Scanlan, Attorney-at-LawBinary measures of group differences in health outcomes vary, depending on the prevalence of the outcome. For example, as mortality declines, relative differences in mortality tend to increase, while relative differences in survival tend to decline. Measures that are functions of binary outcomes (e.g., gini coeffi-cients and longevity differences) also tend to change in some man-ner as the prevalence of an outcome changes. This renders prob-lematic efforts to evaluate the size of health disparities at different times or in different settings, with measures based on mortality or morbidity rates. It is possible that continuous variables may offer approaches to measuring the size of group differences in health that are independent of changes in prevalence of the factor being examined. But that possibility must be tested, and factors that are useful to examine need to be identified.

Tuesday, July 31Time: 7:00 a.m. – 8:15 a.m.





als when transitioning from graduate school to the “real world.” Topics to be considered include networking, job interviews, financial realities, workplace dynamics, and career development. An underlying theme concerns how to understand the similari-ties and differences between academic and work environments to overcome common challenges. The moderator in this case has six years of professional experience after graduate school, so can offer his perspective. It is intended that participants be able to share their experiences with the group in a conversational setting.


TL07 Ideas for Improving Appreciation and Understanding of Cluster SamplingWinston A. Richards, The Pennsylvania State University, HarrisburgHealth researchers must master basic principles and methods for critiquing and producing health research literature efficiently; thus, they need to understand various methods of sampling. Two recent articles in the February 2007 issue of The American Statistician, one by Alf and Lohr and the other by Strasak et al., can motivate discussion about how to introduce these concepts to

students in the health sciences. Al and Lohr review the treatment of sampling assumptions for confidence intervals and hypothesis tests in several texts. They identify strengths and flaws and pro-pose promising approaches to teaching simple random sampling, cluster sampling, and confidence intervals. Strasak et al identify related errors that show up in medical research articles. They provide a quality improvement checklist for statistical evaluation of medical manuscripts.

TL08 Interpreting Statistical Results from Medical Literature in the Classroom Kirk Anderson, Grand Valley State UniversityIf you are considering the use of medical literature in your class-es, or have experiences to share, join us for coffee and discussion. Issues may include how/where to look for articles, who should conduct the search, how to handle mistakes or complicated methods, and what to ask to assess student comprehension. I am a statistics professor with experience teaching introduc-tory statistics to graduate students who are typically biologists, nurses, occupational therapists, physical therapists, and physi-cian assistants.

StudentMixerMixer Monday, July 306:00 p.m.–7:00 p.m.The Grand America Hotel Venezia Garden Salon


roundtable is intended to discuss why we write these documents, who the target audiences and reviewers are, when in the lifecycle of a trial do we write these, are they really necessary, and how easy/difficult they are to put together.

TL12 JAMA Policy on Independent Analysis and Public Trust Hong Liu-Seifert, Eli Lilly and CompanyJAMA’s policy requires independent analysis by independent stats for industry-sponsored papers. Join us for an open and productive discussion about approaches to address similar poli-cies and transparency issues and to improve public trust in our industry as a whole.

TL13 Blinded Sample Size Re-estimation Biao Xing, GenentechBlinded sample size re-estimation allows for modifying the sample size of an ongoing trial to ensure sufficient statistical


TL10 Joining the Evil Empire: What It’s Like To Move from Academics to Industry Robert Parker, Amgen Inc.For all the academics out there secretly wondering what it’s like in industry, this roundtable will answer your questions. Secrets will be revealed! Learn some of the good—and bad—of industry from someone who recently changed sides.

TL11 Statistical Analysis Plans: How, When, Why, and for Whom Do We Do Them? Bruce Binkowitz, Merck Research LaboratoriesStatistical analysis plans (SAPs) are suggested by guidance (e.g., ICH E9) as appropriate documents for prespecifying statisti-cal methodology and data-handling rules. These analysis plans should be completed prior to the unblinding of a database. This

Business and Economics Statistics SectionOrganizer: Badi H. Baltagi, Syracuse University

TL09 The Use of Birth Panel Data in Economic Research Jason Abrevaya, Purdue UniversityThe use of maternally linked birth data (at the federal and state levels) for economic research will be discussed. Specific applica-tions, including the effects of public policy (e.g., cigarette taxes) upon prenatal behavior and the effects of child gender mix upon fertility outcomes, will be discussed.

Speaker with Lunch

Tuesday, July 31Time: 12:30 p.m.–1:50 p.m. Regular–Traditional Caesar salad; boneless breast of

chicken topped with a pear tomato marinara sauce, sprinkled with mozzarella and Romano cheeses, and served over penne pasta; New York style cheesecakeVegetarian–Traditional Caesar salad; breaded eggplant with parmesan and mozzarella cheese served with a side of linguini topped with roasted pear tomato coulis; fruit cup dessertChef’s choice of kosher and heart healthy menus also available



Jason Abrevaya will be a professor of economics at the University of Texas starting in fall 2007. Previously, he held positions at Purdue University’s Krannert School of Management and the University of Chicago’s Graduate School of Business. His area of special-ization is microeconometrics, and he has published articles in both theoretical and applied econometrics. His main areas of interest include demographics and health, labor, and sports economics.

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American Statistical Association

Presidential Address &Awards Session

Mary Ellen Bock, ASA PresidentTuesday, July 31, 8:00 p.m.Salt Palace Convention CenterBallrooms E-J

★ Statistics in Chemistry Award★ ASA Fellows★ Founders Award★ Outstanding Statistical Application Award★ Statistical Partnerships among Academe, Industry, and Government (SPAIG) Award

Is your associate, professor, student, colleague, friend, or organization being recognized at the Joint Statistical Meetings in Salt Lake City?

Plan to attend the ASA Presidential Address and Awards Session for the recognition of the ASA’s most distinguished members.

Samuel S. Wilks Memorial Award

Edward C. BryantScholarship

Gertrude M. CoxScholarship

Gottfried E. NoetherAwards

W. J. Youden Award in Lab Testing


developed to measure the impact of the approach on the quality of analysis and the associated risk.

Section on Health Policy StatisticsOrganizer: Anirban Basu, The University of Chicago

TL18 Recent Methodological Developmentson Prediction of Health Care Costs Xiao-Hua (Andrew) Zhou, University of WashingtonIn this roundtable, I will discuss the difficulty of predicting future health care costs of individual subjects due to their special distri-butional features, including skewness, zero, and heteroscedasticity. Then, I will discuss recent attempts to overcome these difficul-ties—including parametric, semiparametric, and nonparametric models—and contrast their strengths and limitations. If time allows, I will illustrate these methods in a real clinical study, con-ducted in the population of U.S. veterans.

TL19 Statistical Methods for Measuring Workfl ow and Workload in Medical Care Systems Jimmy Efird, John A. Burns School of MedicineMillions of dollars have been invested in complex information technology systems to improve patient outcomes, enhance bedside care/patient monitoring, and minimize drug-dispens-ing errors throughout the medical care system in the United States. Unfortunately, rigorous statistical methods are not used to ascertain the impact these new technologies may have on the workflow and workload of medical staff, which involves changes in their time and task commitments, following related changes in the work environment. Often, these new systems are removed from clinic floors, following numerous complaints from doc-tors and nursing staff. This luncheon will focus on the statistical methodology for conducting workflow and workload analysis. Topics discussed will include measures of accuracy and reliabil-ity, sampling methodology, categorical responses, and repeated measures designs.


TL20 Challenges in Mixture Experiments Greg Piepel, Battelle/PNNLA mixture experiment (ME) involves mixing components to form an end product and measuring a response, which depends on the proportions of the components and maybe other fac-tors (e.g., total amount and process variables). Methods for ME design and analysis have been developed over the last 50 years. However, challenges often exist for ME problems. One challenge is to decide which approach is best for a given ME problem. Another challenge might be a “twist” in the ME or its data analy-sis not addressed by existing methods or software. Roundtable participants should come prepared to briefly describe one or two challenges they have faced in ME problems, what they did to address the challenges, and whether new methods or software capabilities are needed. The opportunity for discussion and feed-back from other participants should make this an interesting and useful roundtable.

power without breaking the blind. One challenge is the blinded estimation of the within-group variance. Early proposed meth-ods either make untenable assumptions or are applicable to only two-treatment trials. Moreover, these methods are often biased. We propose a simple, unbiased method that also makes minimal assumptions. The method uses the enrollment order of subjects and the randomization block size to estimate the variance and then re-estimate the sample size. It can be applied to normal or non-normal data, to trials with two or more arms, equal or unequal allocation schemes, and fixed or random randomization block sizes. Results from simulations and data analysis suggest the proposed blinded sample size estimation approach is practical.

TL14 Estimation of Treatment Effects in Randomized Trials with Noncompliance and Crossover: Why ITT Analysis May Not Be Our Best OptionAfisi S. Ismaila, McMaster UniversityWhen there are departures from assigned treatments in a ran-domized controlled trial (RCT), researchers are faced with esti-mating treatment benefits in compliant and crossover patients while respecting randomization. We will discuss why some of the well-known traditional approaches may not be our best option. We also will discuss some of the newest approaches for dealing with this problem.


TL15 Meta-analysis of Diagnostic Tests Vanja Dukic, University of ChicagoThe purpose of this roundtable is to gather researchers interested in meta-analysis and facilitate a discussion about recent statisti-cal methods for evidence synthesis, with the focus on medical decisionmaking. Particular attention will be given to methods for Bayesian meta-analysis of diagnostic test studies. Meta-analysis software also will be discussed.

Section on Government StatisticsOrganizer: Michael E. Davern, University of Minnesota

TL16 Data User Issues with the American Community Survey (ACS)Patricia Becker, APB AssociatesAlmost a year ago, we saw the release of the first full year of data collection, the 2005 ACS. Data were released in several formats on American FactFinder. What are user experiences with these products? How can they be improved? What should we expect the U.S. Census Bureau to do so the products work better for us?

TL17 Remote Access to Microdata Julia Lane, NORC at the University of ChicagoThis roundtable will focus on discussing the costs and benefits of providing researchers with remote access to microdata. It will describe the implementation at NORC using the National Institute of Standards and Technology’s Advanced Technology Program data. It also will describe some of the metrics being


Section on Statistical ConsultingOrganizer: James Grady, The University of Texas Medical Branch

TL24 Alternative Models for Consulting Services in Academic Medical Centers Shelley Hurwitz, Harvard Medical SchoolAs acknowledgment of the value of statistics in medical research expands, the need for statistical services grows. This will be an informative discussion for statisticians involved in consulting ser-vices at academic medical centers and for those considering such involvement. The organizer designed and directed two consulting services at an academic center associated with Harvard Medical School, with different operating models and fee structures. One had a large number of independent consultants over six years. The other had a smaller number of statisticians on staff for three years so far. Participants involved in consulting services will have the opportunity to describe their experiences. Attendees will learn what works and what does not and benefit from the experiences of the group in creating and/or participating in consulting services at academic medical centers.

TL25 Statistical Consulting in Medical Devices: Opportunities and Challenges Jianxiong Chu, U.S. Food and Drug AdministrationMedical devices are as vital to drugs to prevent, diagnose, and treat diseases. The device industry has developed life-saving and life-enhancing products, such as pacemakers, artificial joints/hips/spinal discs, and drug-eluting stents. Recent scientific advances in bioengineering, biomaterials, genomics, and nanotechnology may accelerate the innovation of new medical devices for delivering high-quality health care. In this roundtable, I will briefly describe the differences between drugs and devices to kickoff the discussion about the opportunities and challenges of statistical consulting in the development of new medical devices. For those who have been involved in medical devices, please come and share. For those of you who have not been involved but want to, please also come and learn more about the exciting field of medical devices.


TL26 My Favorite Case Study Laura Chihara, Carleton CollegeDo you have a favorite case study from a scholarly journal, news-paper, or magazine that you use in an introductory statistics class? We invite you to share this case study with others and join a discussion about using case studies effectively in a small classroom setting.

TL27 Group Work and How To Assess It William Harkness, The Pennsylvania State UniversityI love having students do group projects, but are they valid assessment measures? Studies have shown that collaborative group work results in improved student performance (and I believe this). However, should scores on group projects be used in assigning grades? What are the pros and cons of doing so? Let’s discuss this!

TL21 Drug Discovery and Cheminformatics: Advances, Challenges, and Frontiers Jacqueline M. Hughes-Oliver, North Carolina State UniversitySix exploratory centers for cheminformatics research were established in 2005. These centers serve as precursors to full-scale cheminformatics research centers for the development of computational algorithms, software tools, theoretical insights, and data-rich resources applicable to chemical diversity and high-throughput screening. A major challenge issued in the NIH request for application was to create cross-disciplinary teams to bring new insight for addressing the difficult problems within cheminformatics. Statisticians have been taking a leading role and making major contributions toward this effort. This round-table will discuss advances, challenges, and frontiers in chemin-formatics research. Folks from other areas who manage or are involved in similar cross-disciplinary efforts also are welcome.


TL22 Tools for Planning and Properly Sizinga Factorial DOE Shari Kraber, Stat-Ease, Inc.Newcomers to factorial design find it difficult to choose appro-priate designs with adequate power. During this luncheon, we will discuss a clear process to determine the best design for the problem. Attendees are welcome to bring their planning pro-cesses to share with the group. A discussion of statistical power will demonstrate how the size of the effect relative to the noise is a critical criterion in design selection. We also will discuss how to choose ranges for the input factors, the importance of evalu-ating aliases, and checking runs for safety. Various case studies will illustrate the importance of using a planning process to avoid DOE failure due to an incorrect design choice. Attendees will take away a variety of strategies for determining which factorial design is appropriate for their data analysis needs.

TL23 Teaching Experimental Design to Students Planning an Industrial Career John Lawson, Brigham Young UniversityWe will discuss topic emphasis in experimental design classes taught for students planning a career as an industrial statistical consultant. Software has made both the construction of experi-mental designs and analysis of the resulting data much easier. Therefore, students planning industrial careers have less need to focus on the hand-computational formulas or algorithms to construct certain types of designs presented in many traditional experimental design texts. More time could be spent on teaching students, a strategy for selecting a design that is appropriate for the research objective, how to recognize the appropriate error term for hypothesis testing, and how to interpret and present results that will be meaningful to nonstatisticians. Participants should be prepared to discuss their experiences and share what they have found to be effective.


TL28 What Is So Great about Service Learning (SL), and How Much Work Is It? Amy Phelps, Duquesne UniversitySupport for SL activities in higher education is growing. SL projects fit with the GAISE guidelines, but how does one use SL, how much work is it, and what do students gain? Student projects may achieve goals of the GAISE guidelines, but may lose the social relevance of data in the real world. Anderson (1999) emphasizes when a “project comes from a local source, students’ interest and ownership of the project is strong.” SL incorporates reflection assignments to further strengthen student learning. SL projects require more effort, but students benefit from seeing the instructor fully engaged, expectations are higher to meet client needs, and students rise to the occasion. The process begins early and unfolds throughout the term. Positive outcomes are realized in student development and service to a nonprofit in need of statistical support.


TL29 Managing the Biostatistics Consulting Service in an Academic Hospital Dianne M. Finkelstein, Harvard/MGHA biostatistics consulting service can be an opportunity for devel-oping new collaborations in a research hospital. However, it also

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can present challenges in terms of balancing priorities and time. This roundtable will be a discussion of how best to handle these challenges. In addition, we will talk about choices, such as how to charge for the service, required training, and the role of educating the investigator.


TL30 From Soft to Hard Science: Will Survey Research Make the Transition? Robert Fay, U.S. Census BureauApart from my “day job,” I have studied scientific communica-tion for several years and begun describing myself as a “daytime statistician/nighttime scientist.” I’d like to informally share some of my reflections on the state of survey research that stem from my investigations. Both scientists and the public occasionally distin-guish “soft” and “hard” science without firmly agreeing on how or where to draw this boundary. I suggest disciplines and individual researchers can be divided linguistically by the discourse structure of their writing. In the last century, the “hard” sciences have shared common communication standards that are much less reliably observed in “soft” science. But, change is possible. I will point to disciplines where the soft to hard transition has occurred or is tak-ing place and what survey research could learn from them.


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with multivariate statistics. I’ll demonstrate a method used at Macalester College to teach introductory-level students the sta-tistical concepts they need to think about multivariate relation-ships. The method relies on graphics and geometry and makes it much easier to understand in a concrete way seemingly abstract ideas, such as multi-colinearity, and seemingly advanced meth-ods, such as analysis of covariance. The graphics and geometry open up the “black box” of multivariate statistical modeling so nonmathematically oriented people can use the techniques effec-tively and with understanding.

Section on Statistics and the EnvironmentOrganizer: Andrew B. Lawson, University of South Carolina

WL04 Multivariate Environmental Health Surveillance Andrew B. Lawson, University of South CarolinaIn surveillance of environmental risk, there is a need to consider the linkages between various inter-related outcomes. For example, in health risk assessment, we might be interested in monitoring comorbidity or alternative markers of variation in risk. This area is closely related to syndromic surveillance, where ancillary variables are used to make early predictions of adverse risk scenarios. In the spatial domain, the task is essentially the monitoring of spatial distri-butions of risk variables and their surrogates. The similarity to sur-rogate biomarker endpoints is marked. Hence, multivariate spatial models could be envisioned where prospective modeling will be the main focus. Ancillary time series also would be jointly modeled.

WL05 Bayesian Disease-Mapping Methods and Applications: Past, Present, and Future Ying MacNab, University of British ColumbiaBayesian disease-mapping methodology has seen enormous devel-opments in the past decade. Statistical models and methods of infer-ence have been developed to facilitate univariate, multivariate, and spatiotemporal disease and health outcome analysis and mapping. The intent of this roundtable is to provide a venue for statisticians working on disease mapping to share their thoughts about this very active area of research, both in terms of the methodological devel-opments and their timely applications in health science and envi-ronmental studies, such as cancer and disease epidemiology, health services utilization and outcome evaluation, and population and public health risk assessment, to name a few. It is hoped that statisti-cians will find this a worthwhile, informal, and engaged discussion.

Wednesday, August 1

Section on Risk AnalysisOrganizer: Susan Simmons, The University of North Carolina at Wilmington

WL01 Assessing Risks in the EnvironmentEdward Boone, Virginia Commonwealth UniversityWhen assessing risks in environmental and ecological settings, there are often many criteria by which we can measure risk. Unlike the business and financial arenas, where monetary risk is an easy and obvious quantity to measure, environmental and ecological risks have no obvious quantity. This is important when approaching policymakers who will spend money to clean up or protect ecosystems. Do the risks outweigh the costs to take action? In this roundtable discussion, we will discuss this quan-dary and brainstorm how to determine a better measure of risk.


WL02 Study Design in Statistics Education Felicity B. Enders, Mayo Clinic College of MedicineThe emerging multidisciplinary field of statistics education has been home to a variety of study designs, in part because random-ized trials may be difficult, or even unethical, in the classroom. Consequently, the goal of this roundtable is to brainstorm regard-ing ideal study designs for statistics education. In order to jump-start the discussion, we will review study designs used in articles from the Journal of Statistics Education, the Statistics Education Research Journal, and The American Statistician.


WL03 Introducing Multivariate Statistics through Graphics and GeometryDaniel Kaplan, Macalester CollegeReal-world problems are almost always multivariate, but most people’s mathematical background doesn’t prepare them to work

Wednesday, August 1Time: 7:00 a.m. – 8:15 a.m.






WL06 Methods for Missing Data in Survey ResponseXiaoming Sheng, University of UtahMissing data problems persist in many scientific investigations. Various strategies for analyzing missing data have been proposed, but are limited to data on continuous measurements. This round-table will focus on some of the available strategies to analyze item response data in survey response. In particular, we will investigate the effects of popular missing data methods on various miss-ing data mechanisms. Large sample behaviors of estimators in a simulation study that evaluates and compares their performance and data from a quality-of-life survey of lung cancer patients will be used to illustrate the utility of these methods. Participants are welcome to talk about their experiences during the discussion.


WL07 Biostatistics Curriculum for National Institutes of Health (NIH) Training Grants: Training, Expectation, and Outcome Madhu Mazumdar, Cornell UniversityMany NIH training programs in clinical and translational research emphasize development of courses in biostatistics. (Co-) Mentoring from biostatisticians for the clinical research training project also is encouraged. Biostatistics faculty and staff at aca-demic medical centers often have to develop and/or participate in these programs. The goal of this session is to discuss how much training time is allocated for biostatistics, what kind of statistical training is needed to be a successful independent researcher, what the most appropriate text books are, what statistical software is most adequate, what % FTE support do biostatisticians derive from training grants, and what the byproducts of these mentoring experiences are. I will share my opinions about these issues and would like to gain from the experience of other statisticians.

WL08 Balancing Teaching and Research: Statistics in the Health Sciences Novie Younger, The University of the West Indies at Mona, JamaicaCollaboration with researchers in the health sciences provides teaching sessions that are relevant examples of applied statistics for biostatistics. Such didactic sessions can be highly interactive through discussion of the limitations and benefits of various statis-tical methods. The different audiences—epidemiology, nutrition, and basic medical sciences graduate students and health workers attending short research skills courses or following degree pro-gram modules—achieve heightened awareness of the relevance of the various tools to their own career development. Adequate preparation for beneficial teaching may, however, encroach upon time and resources that should be used for research. For this cof-fee session, we will discuss the possible need to balance the time and resources academic statisticians devote to teaching versus research and ways to achieve this balance.

Register in Advance for the JSM Career Placement Service and Get a Head Start!

New This YearAll preregistered applicants will get ADVANCE online access to job postings as they are posted!

Starting June 1, you will be able to access our searchable online job postings and contact inter-viewers who will be onsite at the JSM Career Placement Service. Save hours of reviewing job listings onsite. Come prepared to meet with the employers of interest to you!

Preregister by July 12 and Enjoy:• Access to our online job postings, beginning on

June 1

• Contact information for the majority of onsite interviewers for top statistical employers

• Immediate access to the Career Placement Service when we open Sunday, July 29

Past Employers: Google, Abbott Labs, Capital One, Eli Lilly and Company, the U.S. Food and Drug Administration, Mayo Clinic, the National Security Agency, PPD, and SAS


WL11 Clinical Trial Simulation: Beyond StatisticsBret Musser, Merck Research LaboratoriesCan statistical modeling and simulation improve decisionmaking in drug development? As we industrialize our approach to clinical trials, how should we—statisticians—be involved in bringing order to the chaos of how to design clinical development programs?

WL12 Statistical Concerns and Methodology Regarding Radiographic Data in Rheumatoid Arthritis (RA)Lifen Zhou, Amgen Inc.Radiographic data are commonly used to assess structural joint damage in RA. The use of statistics to analyze this data is important, and often needs additional consideration due to the


WL10 Incomplete Data in Longitudinal Studies Geert Molenberghs, Hasselt UniversityMost, if not all, clinical and nonclinical longitudinal studies are subject to incompleteness. In a biopharmaceutical context, a lot of relatively simple methods for dealing with such incomplete data have been in use. On the other hand, ever more advanced meth-ods for handling incomplete longitudinal studies are proposed by the research community. Regulatory authority-based, biophar-maceutical, and academic researchers need to work together to bridge this gap and move on. What would be viable strategies to achieve this goal?

Health Policy Statistics Organizer: Anirban Basu, The University of Chicago

WL09 Importance of Using Cost-Effectiveness Analysis to Inform Health Policy in the United States David Meltzer, The University of ChicagoWith the increasing level of health spending in the United States, there has been increasing interest in the use of cost-effectiveness analysis (CEA). CEA is an attractive tool; it provides information about the value of medical technologies relative to their cost, pro-viding data to maximize health benefits for any level of spending and enabling public policy analysts to make efficient allocations of resources. CEA has not yet played a major role in shaping medi-cal coverage decisions in the United States, but it already plays a role in other countries, and the introduction of the Medicare Modernization Act creates the opportunity for CEA to play a role in United States policy. One barrier to increasing the role of CEA in United States health policy is concerns about the validity of methods. This talk will discuss the conceptual, theoretical, and methodological challenges in CEA to inform discussions of its use in the United States.

Speaker with Lunch

Wednesday, August 1Time: 12:30 p.m.–1:50 p.m. Regular–Spinach salad; boneless breast of chicken

prepared with sliced mushrooms, artichoke hearts, and capers in a lemon butter sauce and served with Minnesota wild rice pilaf; carrot cakeVegetarian–Spinach salad; red bell pepper stuffed with mild mushroom and tri-colored tomato orzo served with polenta, seasonal vegetables, and roasted garlic marinara; fruit cup dessertChef’s choice of kosher and heart healthy menus also available



David Meltzer is associate profes-sor in the Department of Medicine, Department of Economics, and Harris School of Public Policy Studies and director of the Center for Health and the Social Sciences (CHeSS) at The University of Chicago. He earned his MD and PhD in economics from The University of Chicago and complet-ed his residency in internal medicine at Brigham and Women’s Hospital in Boston. A major area of Meltzer’s research examines the theoretical foundations of medical cost-effective-ness analysis, including issues such as accounting for future costs due to the extension of life and the empirical validity of quality-of-life assessment, which he has examined in the context of diabetes and prostate cancer.

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WL16 The Quasi-Bayesian Approach to Risk Management at the Department of HomelandSecurity (DHS) David Banks, Duke UniversityThe DHS uses a somewhat Bayesian approach to risk manage-ment. We will outline what is currently done, and then open the floor for creative conversation. Some of the issues that arise include risk analysis, subjective probability, the Kadane-Larkey approach to game theory, and portfolio theory for maximizing return on defen-sive investments.


WL17 Verifying Computer Experiments with Physical Experiments William Notz, Ohio State UniversityComplex computer simulations have become popular substitutes for physical processes that are expensive or difficult to observe. Experimenting with computer simulation as a means of studying the physical process is called a computer experiment. For this approach to yield meaningful results, the computer simulation must be a rea-sonable approximation to the physical experiment. Verifying this is sometimes referred to as validating the computer experiment. This session will consider methods for validating computer experiments. There is only a modest literature on validating computer experi-ments. We will discuss the current state of the literature, related problems (e.g., calibration and combining data from multiple sourc-es), and possible research directions. A bibliography of some of the literature that exists will be provided.

WL18 Publishing an Industrial Case Study: Advicefor Would-Be Authors Robert Rodriguez, SAS Institute Inc.Good published case studies of industrial statistical applications are in high demand by practicing statisticians and classroom instruc-tors, but they are in short supply. This is partly because many statis-ticians working in industry are not encouraged or prepared to write for journals. We will discuss success factors for publishing industrial case studies (such as an application of general interest and statistical substance) and how to approach the writing process. Join us if you have material you would like to publish, or if you are affiliated with a journal that would like to attract industrial case studies.


WL19 Communicating with Nonstatisticians Mark Bailey, SAS Institute Inc.Discuss and share your ideas about the best ways to communicate statistical results to nonstatisticians in the context of the client-stat-istician relationship. This discussion will include experiences from successful and failed collaborations. In particular, we want to know what worked well and what didn’t.

nature of radiographic disease progression. Key characteristics of this data will be highlighted. Statistical methodology in this area will be discussed, including the standard rank method, such as Wilcoxon rank; covariates adjusted method, such as Quade; and the strata variables adjusted method, such as Van Elteren.

WL13 Design-Based, Multiplicity-Adjusting Strategies in Late-Phase Clinical Trials Jianjun Li, Merck Research LabsIn clinical trials, endpoints are classified as primary, secondary, etc. To control trial-wise, type-I error, the Hochberg procedure is commonly used for handling multiple testing among primary endpoints. For secondary endpoints, which can be used for regulatory claims but are potentially underpowered, the PAAS has been proposed. For secondary endpoints, which play only a supportive role, gate-keeping procedures have been developed. While these procedures are proposed for general use, they do not incorporate a unique characteristic of late-phase clini-cal trials: The primary endpoints are powered by design. This discussion will focus on how to utilize this important property in the analysis of multiple endpoints. Recent developments in statistical methodology and their impacts on clinical trials such as CAPRICORN trial, ATLAS study, DEFINITE trial, and PROactive study, will be included.

Business and Economics Statistics SectionOrganizer: Clifford M. Hurvich, New York University, Stern School of Business

WL14 Model Selection David Findley, U.S. Census BureauSince Mallows, Akaike, Schwarz, and Rissanen introduced their model selection criteria, there has been steady growth in the related literature, developing variants of their now classical criteria, as well as alternative criteria, for situations involving small samples, robust or suboptimal estimation methods, semi-parametric models, mis-specified models, etc. We will talk about practical model selection problems and these newer criteria.

WL15 Statistical Analysis of Large Panelsof Economic DataSerena Ng, University of MichiganMore economic data are available for analysis as we move for-ward in calendar time and as technological progress makes it possible to collect information about more series. Developing statistical methods that can efficiently exploit the large volume of information available is therefore important. In this session, we will discuss statistical methods for analyzing large panels of economic data. While principal components is often used to reduce the dimension of economic time series, methods such as regularization (e.g., LASSO) and adaptive learning (e.g., boosting) are more popular in machine learning and gene clas-sification. We will discuss the strengths and weaknesses of these methods, with emphasis on their role in economic forecasting and financial analysis.


WL20 Risk-Adjusted Charts in Health Care MonitoringLandon Sego, PNNL-BattelleStatistical process control (SPC) is making notable inroads in the health care industry. The application of SPC we will con-sider here involves monitoring the mortality associated with a health care procedure, which, in order to be effective, requires accounting for the fact that the risk of mortality for each patient depends not only on the quality of the procedure, but also on risk factors unique to each patient that exist prior to the procedure. Incorporating these risk factors (covariates) into the monitor-ing scheme is known as risk adjustment. We will discuss the risk-adjusted varieties of several well-known charts: Shewhart p-chart, the Sets method, the resetting SPRT, and the Bernoulli Cusum chart. We also will discuss a new risk-adjusted Cusum chart for monitoring right-censored survival times and consider areas of future development.

Section on Statistical ConsultingOrganizer: James Grady, The University of Texas Medical Branch

WL21 Recognizing and Resolving Breakdownsin Your Consulting Practice Doug Zahn, Florida State UniversityBreakdowns are a natural part of everyone’s consulting practice. No matter how carefully we plan and communicate, breakdowns (i.e., failures of the conversation, project, process, etc., to function as intended) will inevitably occur in encounters with our clients, colleagues, supervisors, and staff. In this luncheon, I will introduce you to a process for recognizing and resolving your breakdowns. You will have an opportunity to use it to identify at least one step you can take to resolve your most vexing, repeater breakdown.

Section on Statistical EducationOrganizer: Jacqueline Miller, The Ohio State University

WL22 User-Friendly Jargon for Statistics Larry Weldon, Simon Fraser UniversitySignificant results that are not important, normal distributions that are not usual, standard deviations that are not acceptable, regression that is not a backward step, expected values that never occur - these common occurrences have the potential to confuse all but the most indoctrinated statistician. And then we verbalize our descriptions of these things in a foreign language using Greek letters. Is there a fix to this disastrous marketing of our discipline?

WL23 Statistics and Research Design: Oil and Vinegar?Seth Hirshorn, University of Michigan-DearbornProposal writers and reviewers are rich with stories of proposals awarded or unfunded based on either a project’s research design and/or its data analysis (a.k.a. statistics) sections. We will tap these stories during this roundtable. The intersection of these is critical to many research proposals, yet often an overlooked and/or separately produced (stove-piped) component. The pur-pose of this discussion is to examine the requirements funding agencies have in the research design and data analysis areas and examine both failed and successful strategies for the integration of research design and data analysis in funding proposals. The focus will be on “evaluation” proposals of government, human service, and education programs. Proposal writers and readers with case studies to share are invited.

Bringing the ASA to Salt Lake City

Discover the benefi ts of membership

Visit the ASA BOOTH at JSM and learn about the many programs available to you. Within the ASA Communities Booth, you can hear about:

SECTIONS—Get information about 22 Sections that encompass several special interests in statistics

PUBLICATIONS—Flip through the ASA’s journals and magazines or pick up brochures about various ASA programs

MEMBERSHIP—Ask an ASA staff member questions about the Association or member benefi ts


WL24 Academic Integrity in a High-Tech Classroom John McKenzie, Babson CollegeTechnology is an integral component of any applied statistics course today. But, there is a dark side to the omnipresence of technology. With the increasing ability of students to communicate with others in and outside of the classroom, the possibility of academic integrity violations increases. In a wireless environment, this illegal exchange of information may be accomplished by using a laptop, PDA, or even a cell phone. And, while an instructor may ban PDAs or cell phones, it is difficult to restrict laptops when students are using them for calculations or note-taking. This roundtable will discuss ways to reduce such unauthorized collaboration when laptops are allowed in the classroom. Among the preventative measures to be discussed are blocking devices and electronic quizzes and examina-tions. If time permits, other examples of inappropriate use of tech-nology will be considered.


WL25 Visualizing Model and Parameter UncertaintyDavid W. Scott, Rice UniversityUnderstanding the uncertainties of model parameter estimates and corresponding model sensitivities with many parameters offers an excellent opportunity for visualization experimentation. We will begin with topics in regression and mixture models.

Section on Statistics in Defense and National SecurityOrganizer: David J. Marchette, Naval Surface Warfare Center

WL26 Text Data Mining for Defense Applications Jeffrey Solka, Naval Surface Warfare CenterThis roundtable discussion will explore the role of text data min-ing in defense applications. Discussions will include, but not be limited to, the role of text data mining in the characterization of country capabilities, its role in the characterization of the state of the art of a discipline area, and its role in discovery. Discussion will focus on the speaker’s experiences in this area and his knowl-edge of the state of the text data mining literature. We also will explore who the customers might be for these techniques and where the future lies, both in the technology and the important problems that have not yet been addressed.


WL27 Longitudinal Causal ModelingJames Robins, Harvard School of Public HealthIn longitudinal studies with time-varying treatment, the standard approach to the estimation of the effect of treatment on an out-come of interest is to model the outcome at time t as a function of past treatment history. This approach may be biased, whether or not one further adjusts for the past history of time-dependent confounding covariates, when these covariates predict subsequent outcome and treatment history and are influenced by past treat-ment. In this roundtable, I will discuss several methods that can provide, under certain assumptions, valid estimates of the causal effect of a time-varying treatment in the presence of time-varying confounding factors. These include inverse-probability-of-treat-

ment-weighted (IPTW) estimation of a marginal structural model, g-estimation of a structural nested model, and the parametric g-computation algorithm. The three methods will be compared.


WL28 Auditing Election Results Wendy Rotz, Ernst & Young LLPVoter confidence and transparent elections are essential to mod-ern democracies. A statistical foundation in the development of election auditing procedures would aid transparency and improve voter confidence in election results and the democratic process in the United States and abroad. Statistical issues may include 100% recounts in close elections, random recounts in all elections, paper trails, Six Sigma applications from quality pro-cess control, exit polling, and many more. Share ideas concerning statistical methodologies for auditing election results.


WL29 Media Coverage Regarding Dataon Mortality in Iraq Leslie Roberts, Columbia Mailman School of Public HealthBetween May and July 2006, a national mortality survey was con-ducted in Iraq. The results were reported in The Lancet in October 2006. The survey found that by July 2006, there had been 655,000 (CI: 393,000–943,000) excess deaths above the pre-war baseline in Iraq as a consequence of the war. Media coverage of the results emphasized the controversial nature of the study, in spite of the conventional methods employed, and has continued to focus on lower surveillance estimates based on morgue and hospital records. This is because of the difficulties of communicating sample results, the extremely incomplete nature of vital record-keeping in settings of extreme violence, and successful spinning of the story by parties with nonscientific agendas. The discussion leader will outline his experiences with the press as an author of this study.

Statistical Society of CanadaOrganizer: X. Joan Hu, Simon Fraser University

WL30 Fifty Years of Empirical Bayes/Shrinkage Inference: Past, Present, and Future Outlook Syed E. Ahmed, University of WindsorEmpirical Bayes (EB) and shrinkage estimation methods surfaced in statistical literature about 50 years ago. Shrinkage and EB meth-ods provide useful techniques for combining data from various sources. Very large gains in inferential accuracy may be achieved by judiciously employing these strategies. It seems inconceivable, then, that not much attention has been paid to these methods in the development of statistical theory. Current statistical prob-lems in the high-dimensional and low-sample size settings have regenerated interest in these techniques. These methods continue to play vital roles in statistical inference, and continued research through the early 21st century has been predicted. The goal of this roundtable is to bring together frequentist and Bayesian perspec-tives and explore and create common ground.


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Real Salt Lake Soccer GameAdult and Child Price: $23 (Premium Seating)TR02–Saturday, July 28, 7:30 p.m. For the first time, enjoy major league soccer while attend-ing the Joint Statistical Meetings. Don’t miss your chance to see Freddy Adu and the Real Salt Lake take on the New England Revolution (2006 MLS Cup Finalists). Go to http://real.saltlake.mlsnet.com/t121/stadium/seating to view the seating chart.To get to Rice Eccles Stadium, use the University Line of the Utah Transit Authority’s TRAX system. Exit TRAX at the “Stadium” station at 1349 East and 500 South. The station is located at the base of the stadium’s main parking lot. The fare is $1.50.

Utah Gold & Silver TourAdult and Child Price: $59 ($64)TR03–Sunday, July 29, 9:00 a.m.–5:00 p.m.TR13–Thursday, August 2, 9:00 a.m.–5:00 p.m.In 1902, miners searched for gold and silver in the majes-tic Wasatch Mountains. In February of 2002, world-class athletes gathered in Salt Lake City for the 2002 Winter Olympics and in search of gold, silver, and bronze medals. Now is your chance to experience the legacy the miners and Olympians left in Utah. The first stop is Utah Olympic Park, host of the Bobsled, Ski Jumping, Luge, and Skeleton events. During the summer, Aerial Ski Jump training is held here, and the public is invited to watch as athletes practice their “freestyle” jumps and land in an enormous pool of water. Next is Park City, home to the Sundance Film Festival, where guests can learn about its history as a mining boomtown. Lunch is on your own at one of the numerous restaurants along Park City’s historic Main Street. The tour continues through the Wasatch Mountains to the charming Swiss village of Midway, located in the heart of the “Alps” of Utah. Mount Timpanogos towers over the majestic Heber Valley as you enter Provo Canyon en route to Robert Redford’s Sundance Resort. Finally, you will head through Provo and along the front range of the Wasatch Mountains on your way back to Salt Lake City.


Reservation Form and payment must be received by July 12, 2007.All tours include transportation, admissions, and profes-sional guides, coordinated by Western Leisure, DMC.Additional reservations will be taken onsite at the Registration Desk until one hour prior to departure, if there is space available. There will be an additional $5 charged for each ticket purchased onsite.The ASA reserves the right to cancel any tour if the minimum required number of participants is not met. We recommend purchasing tickets for tours in advance.All tours will depart from the Salt Palace Convention Center at 200 South West Temple (south end of the building). Arrive 15 minutes before departure time.Cancellations: A written notice must be received by the JSM Registration Department for the cancellation of any tour reservation. Cancellations received by June 21 will be refunded 80% of the tour cost. Cancellations received June 22–July 12 will be refunded 60%. No refunds will be given after July 12, 2007.

Salt Lake Bees Baseball GameAdult and Child Price: $10.25 (Section 11, Rows 13–18)TR01–Saturday, July 28, 7:05 p.m. The Salt Lake Bees, Triple-A affiliate of the Angels, ended the year as #1 in the PCL Pacific North. This is your opportunity to see the Salt Lake Bees playing against the Iowa Cubs at Franklin Covey Field. The stadium is located at 77 West 1300 South, with the home plate entrance located at the corner of West Temple and 1300 South. Go to www.slbees.com/seat-ingChart.cfm to see the view from the reserved seats.Getting to the stadium is easy via the Utah Transit Authority, TRAX system. It takes approximately 15 to 20 minutes from the Salt Palace Convention Center to reach Franklin Covey Field. Exit TRAX at the “Ballpark” station at 1300 South and walk one block east to the stadium. The fare is $1.50.

Joint Statistical Meetings, Salt Lake City, UtahWELCOMETOURS


Crossroads of the West City TourAdult and Child Price: $20 ($25)TR04–Sunday, July 29, 1:00 p.m.–4:00 p.m.TR05–Monday, July 30, 9:00 a.m.–12:00 p.m.TR09–Tuesday, July 31, 1:00 p.m.–4:00 p.m.Salt Lake City was built out of a desert by the industrious Mormon pioneers. This tour provides a complete look at what makes Salt Lake City so unique. You will begin by seeing the historic downtown area, including world-famous Mormon Temple Square, which took 40 years to build. Next, you will visit the beautifully restored 1908 Union Pacific Depot, featuring French Renaissance archi-tecture and original artwork, before heading outside to enjoy Olympic Legacy Plaza, overlooked by a classic clock tower and featuring the “dancing waters” of the Olympic Snowflake Fountain. On to historic downtown and the residential area known as the “Avenues,” which is listed on the State and National Historic Registers. Next is the University of Utah. The “U,” founded in 1850, was the first university built west of the Missouri River and the site for the 2002 Winter Olympic Athletes Village. Continuing on, guests will ride past Fort Douglas, which was built during Abraham Lincoln’s administration in 1862, and on to This is the Place Heritage Park, where Brigham Young and the Mormon pioneers entered the valley in 1847. Afterward, you will visit Olympic Cauldron Park at Rice Eccles Stadium. Rice Eccles was the site of the Opening and Closing 2002 Winter Olympic Ceremonies. Finally, you return to your hotel with the knowledge that you have had a top-notch overview of Salt Lake City!

Kennecott Copper Mine and Great Salt LakeAdult and Child Price: $27 ($32)TR06–Monday, July 30, 1:00 p.m.–5:00 p.m.TR11–Wednesday, August 1, 8:00 a.m.–12:00 p.m.An exciting tour that is full of contrasts, this tour will begin at “America’s Dead Sea,” the Great Salt Lake. You’ll hear tales of its origin and the many legends the lake has spawned. You’ll also view Saltair Pavilion and have a chance to touch the salty water or buy delicious saltwater taffy. The tour continues along the base of the Oquirrh Mountains, as you make your way to Kennecott’s Bingham Canyon Copper Mine. The largest open-pit mining opera-tion ever undertaken, the Kennecott Mine is one of only two man-made objects visible from space. While there, you’ll have time to visit the Observation Deck and Visitor’s Center and see the actual workings of the mine.

Utah Olympic Park,Park City Main StreetAdult and Child Price: $40 ($45)TR07–Tuesday, July 31, 8:30 a.m.–12:30 p.m.TR12–Wednesday, August 1, 1:00 p.m.–5:00 p.m.In February of 2002, world-class athletes gathered in Salt Lake City for the 2002 Winter Olympics. Now is your chance to see what all the excitement was about. Tour Utah Olympic Park, host of the Bobsled, Ski Jumping, Luge, and Skeleton events. During the summer, Aerial Ski Jump training is held at the facility, and the public is invited to watch as athletes practice “freestyle” jumps and land in an enormous pool of water. You will also tour Park City, which is home to the Sundance Film Festival, and learn about its history as a mining boomtown. Today, Park City is a skiing hotspot and getaway for the rich and famous, yet it retains the charming qualities of a quaint mountain town with a variety of shops on historic Main Street.

Salt Lake Historic Walking TourAdult Price: $11 ($16); Child Price: $0 ($0)TR08–Tuesday, July 31, 9:00 a.m.–12:00 p.m.This tour begins in the historic downtown area, which includes the world-famous Mormon Temple that took 40 years to build. You’ll learn of the trials and triumphs of the pioneers, who transported the granite to build their temple from Little Cottonwood Canyon. Next, you’ll walk through the newly constructed Main Street Plaza to the Joseph Smith Memorial Building. This building was origi-nally built as the Hotel Utah in 1911, and quickly became a beloved landmark. The 10-story building’s classic revival architecture was crowned with an ornate white dome in the shape of a beehive. In 1987, the hotel was retired and refurbished to stand in memoriam of Joseph Smith. The Lion House is next on the list of sites. Noted for the lion above the door, the house was built in 1856 as an extension of the Youngs’ residence, the Beehive House, for Brigham Young and several of his wives and children. The final his-torical sight is Eagle Gate Monument, erected in 1859 as a wood gate and entrance to Brigham Young’s property. In later years, it was replaced by a larger cast iron gate. The original eagle, which once topped the gate, can be found in the Daughters of Utah Pioneers Museum.

Antelope Island and the Great Salt LakeAdult and Child Price: $33 ($38)TR10–Wednesday, August 1, 8:00 a.m.–12:00 p.m.Located in the middle of the Great Salt Lake is an island that has remained pristine since Utah was settled in 1849. This tour will head west across the Great Salt Lake cause-way to visit this island, named Antelope Island, which is home to a unique ecosystem that reflects what the pioneers encountered when they arrived in the Salt Lake Valley. The tour will stop at Buffalo Point, which provides a stunning view of the Great Salt Lake. Today, Antelope Island is home to mule deer, bighorn sheep, antelope, and a herd of 600 bison.

Price in parentheses is for onsite registration.




Employers Seeking Qualifi ed ApplicantsEach year, hundreds of qualified applicants look to the JSM Career Placement Service to begin or further their careers in statistics. Government agencies, academic institutions, and private pharmaceutical firms utilize the JSM Career Placement Service to seek out qualified statisticians. The goal of the Career Placement Service is to make recruiting more efficient and effective for both employers and applicants.

The Benefi ts Speak for Themselves!The JSM Career Placement Service offers employers a full-service recruiting facility during the meeting. Opportunities include:Advance Online Applicant Access – for an addi-tional fee, employers can access applicant information online, viewable and searchable in real time, months before the conferenceOnsite Employer Reading Area – a dedicated spot for employers to relax and review applicant informationComputerized Message Center – allows employers to communicate with applicants throughout the meetingInterview Booths – employers may reserve booths each day in one-hour increments on a first-come, first-served basis throughout the meeting.

CAREER PLACEMENT SERVICE

Applicants Seeking a First or NewStatistical PositionIf you are looking to further your career in statistics, the JSM Career Placement Service can help you get started or get ahead. Hundreds of statistical employers attend JSM each year seeking qualified applicants. All appli-cants receive full access to the JSM Placement Service, including access to the computerized message center and onsite job position books.The Placement Center is open concurrently with the Joint Statistical Meetings. Onsite electronic registration will be available on Saturday; see schedule for details. All participants are encouraged to register by July 12 to maximize their experience and enhance their visibil-ity. Applicants will receive Advance Online Job Posting Access, allowing them to view all job postings from preregistered employers, including job details and the employer number in advance of the meeting. Come to JSM prepared to seek out representatives of your select-ed employers and begin interviewing quickly.

Employer Fees Early ASA Member/ NonmemberMay 1–June 21

Advance ASA Member/ Nonmember June 22–July 12

Onsite ASA Member/ Nonmember July 28–31

Executive Suite $2,250/$2,750 $2,250/$2,750 $2,250/$2,750

Employer Registration $400/$450 $425/$475 $500/$600

Employer Registration with Online Applicant Access

$900/$1,000 $950/$1,100 $1,000/$1,200

Additional Job Postings $50 each $50 each $50 each

Additional Representatives $50 each $50 each $50 each

Applicant Fees Early ASA Member/ Nonmember

Advance ASA Member/ Nonmember Onsite ASA Member/ Nonmember

Regular Registration* $90/$105 $100/$115 $110/$125

Student Registration* $45/$60 $55/$70 $65/$80

* If you wish to interview onsite, you also must register for the JSM. Those registering onsite should pay all meeting and career placement fees at the main registration area. All applicant registrations include online advance access to the job postings. You must provide your own internet access.

HoursSaturday, July 28, 9:00 a.m.–5:00 p.m. OPEN FOR REGISTRATION ONLY. (must have résumé on disk or USB; MSWord, .txt, or .pdf documents only)

Sunday, July 29 1:00 p.m.–6:00 p.m.

Monday‚ July 30 8:00 a.m.–6:00 p.m.

Tuesday‚ July 31 8:00 a.m.–6:00 p.m.

Wednesday‚ August 1 8:00 a.m.–4:30 p.m.

Onsite placement registration closes at noon on Wednesday.


JSM CAREER PLACEMENT EMPLOYER REGISTRATION FORMJSM Career Placement Registration opens May 1, 2007, at www.amstat.org/meetings/jsm/2007/placement

PAYMENT INFORMATION❑ Check enclosed (payable to American Statistical Association in U.S. funds on a U.S. bank)

Credit Card ❑ VISA ❑ MasterCard ❑ American Express

/Credit Card Number Exp. Date CVS # (3-digit # on reverse of card)

Name of Cardholder

Cardholder’s Signature

FAXES OF THIS FORM ARE NOT ACCEPTED. Employers choosing to mail their registration and position postings must complete a Position Description Form for EACH position. Attachments may be included, but must be on disk (MSWord or .txt fi les only, one-page limit). All mail-in registrations MUST be postmarked by July 12, 2007, and sent to JSM Career Placement Service, c/o ASA, Attn: Amy Farris, 732 North Washington Street, Alexandria, VA 22314-1943. Express mail is strongly recommended.

SELECT REGISTRATION TYPE: (select only one)

❑ Executive Suite Registration (# of suites) ________ @ ASA Member $2,250/Nonmember $2,750 $______________

• Suite includes registration fee, online applicant access, 10 job postings, and up to fi ve representatives

• Each suite includes a table and four chairs, a computer and printer, and instant access to applicant data

• The sign on your suite should read: ___________________________________________________________

❑ Early Bird Registration ASA Member $400/Nonmember $450 $______________ May 1, 2007–June 21, 2007 (must be postmarked by June 21)

❑ Early Bird Registration with online Applicant Access ASA Member $900/Nonmember $1,000 $______________ May 1, 2007–June 21, 2007 (must be postmarked by June 21)

❑ Advance Registration ASA Member $425/Nonmember $475 $______________ June 22–July 12, 2007 (must be postmarked by July 12)

❑ Advance Registration with online Applicant Access ASA Member $950/Nonmember $1,100 $______________ June 22–July 12, 2007 (must be postmarked by July 12)

❑ Additional Job Postings (more than fi ve per employer registration/more than 10 per Executive Suite) _______@ $50/ea: $______________

REPRESENTATIVES (up to three per Employer Registration/fi ve per Executive Suite Registration/$50 each thereafter)1. ______________________________________________________ $02. ______________________________________________________ $03. ______________________________________________________ $04. ______________________________________________________ ($0 for Executive Suite/$50 for all others) $______________5. ______________________________________________________ ($0 for Executive Suite/$50 for all others) $______________6. ______________________________________________________ ($50 for all) $______________7. ______________________________________________________ ($50 for all) $______________

TOTAL $______________

CONTACT INFORMATION

Name ____________________________________________________________ ASA ID (must be included to receive member rate)__________________

Employer Name _________________________________________________________________________________________________________

Mailing Address _________________________________________________________________________________________________________

City __________________________________________________State/Province _____________________ZIP/Postal Code _________________

Phone _________________________________Fax _______________________________Email _________________________________________


POSITION DESCRIPTION FORM Complete ONE form per position

AREAS OF INTEREST (select up to three)

❑ Teaching ❑ Social Sciences ❑ Biometrics/Health Sciences ❑ Computing Sciences ❑ Mathematical Sciences ❑ Business/Economics/Management Sciences ❑ Survey Research Methods ❑ Physical/Engineering

TYPE OF ORGANIZATION ❑ Academic ❑ Government ❑ Industry ❑ Recruiter

INTERVIEWS ❑ Will conduct interviews onsite ❑ Will not conduct interview(s) onsite ❑ Allow applicants to contact me in advance

POSITION INFORMATION

Position Title ____________________________________________________________________________________________________________

Geographic Location ___________________________________________ Start Date ❑ Immediate ❑ <6 Months ❑ >6 Months

# of Vacancies ___________

Region ❑ NW ❑ NE ❑ MW ❑ SW ❑ SE ❑ International

SALARY INFORMATION

Starting Salary _________________________________

EXPERIENCE LEVEL ❑ Entry Level ❑ 1–3 years ❑ 4–6 years ❑ 7–9 years ❑ 10+ years

EDUCATION REQUIREMENT (minimum)

❑ Bachelor’s ❑ Master’s ❑ Doctoral Candidate ❑ Doctorate

CITIZENSHIP REQUIREMENTS ❑ U.S. Citizen ❑ Permanent Resident ❑ Nonresident If nonresident, Visa type required _______________________________________________

TRAVEL REQUIREMENTS ❑ No Travel ❑ Some Travel ❑ Frequent Travel

COMPUTER PROGRAMING ❑ ForTran ❑ C/C++ ❑ SQL ❑ Visual Basic ❑ Minitab ❑ JMP

STATISTICAL SOFTWARE ❑ SAS® ❑ SPSS® ❑ MatLab ❑ S-Plus/R®

REQUIRED EXPERIENCE, SKILLS, ETC.

________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________


What Can the JSM Career Placement Service Do for You?The JSM Career Placement Service provides the best opportunity for qualifi ed applicants to meet employers, establish valuable contacts, and learn about organi-zations employing statisticians. Registration for the Joint Statistical Meetings is required in order to interview onsite. To register for the JSM, go to www.amstat.org/meetings/jsm/2007/onlinereg. Once you have registered, go to www.amstat.org/meetings/2007/placement to register for the Career Placement Service. Online JSM and Career Placement Registration opens May 1, 2007.

CAREER PLACEMENT SERVICE OPPORTUNITIES FOR APPLICANTS INCLUDE:

■ Applicant Reading Area—for applicants to review complete job descriptions and contact information from registered employers

■ Visibility to Employers—applicants who register by July 12, 2007, are included in the Advance Applicant Online Database, available to employers prior to the meeting. Employers often contact applicants in advance!

■ Computerized Message Center—allows applicants to contact employers of interest throughout the meeting

■ GET A HEAD START—all applicants receive Advance Online Access to all job postings prior to the meeting! New this year!

Register online starting May 1, 2007, at www.amstat.org/meetings/jsm/2007/placement.

REGISTRATION INSTRUCTIONS AND DEADLINES SELECT REGISTRATION TYPE:

❑ Early Bird Registration—postmarked by June 21, 2007 • Include your Applicant Information Form and résumé in the Advance Online Applicant Access, available to employers prior to the JSM • Online advance access to job postings starting June 1! • Gain immediate access to Career Placement Service onsite!

❑ Advance Registration—postmarked June 22-July 12, 2007 (increased fees apply) • Include your Applicant Information Form and résumé in the Advance Online Applicant Access, available to employers prior to the JSM • Gain immediate access to Career Placement Service onsite!

❑ Onsite Registration—ONSITE ONLY July 28–August 1, 2007 (increased fees apply)After July 12, ALL registrations will be processed onsite. DO NOT mail your registration after July 12. • Onsite placement registration will open at 9 a.m. on July 28 (electronic only) and close at noon on August 1. • Complete the Applicant Information Form and bring your résumé on disk or USB in MSWord or .txt format.

APPLICANT FEES EARLY ADVANCE ONSITE MAY 1–JUNE 21 JUNE 21–JULY 12 JULY 28–AUG 1

Check Appropriate Rate ASA Member

ASANonmember

ASAMember

ASANonmember

ASA Member

ASA Nonmember

Regular Registration* $90 $105 $100 $115 $110 $125

Student Registration* $45 $60 $55 $70 $65 $80

*If you wish to interview onsite, you also must register for the JSM. Those registering onsite should pay all meeting and career placement fees at the main registration area. All applicant registration includes advance online access to the job postings. You must provide your own internet access.

Registration Fee $_________________

PAYMENT INFORMATION

_______________________________________________________________________________________________Applicant Name ASA ID (if applicable, required for member price)

❑ Check enclosed (payable to American Statistical Association in U.S. funds on a U.S. bank)

Credit Card ❑ VISA ❑ MasterCard ❑ American Express

/ Credit Card Number Exp. Date CVS # (3-digit # on reverse of card

Name of Cardholder


All applicants are encouraged to submit their registration online at www.amstat.org/meetings/jsm/2007/placement. Applicants who choose to mail their registrations must complete an Applicant Infor-mation Form and include a résumé on disk (no more than four, single-sided pages; only MSWord fi les or .txt fi les will be accepted). Your registration and disk MUST be postmarked by July 12, 2007. JSM Career Placement Service, c/o ASA, Attn: Amy Farris, 732 North Washington Street, Alexandria, VA 22314-1943. Express mail is strongly recommended.

JSM CAREER PLACEMENT APPLICANT REGISTRATION FORM


APPLICANT INFORMATION FORM

Name ___________________________________________________________________ASA ID (if applicable)_______________________________

Address _________________________________________________________________________________________________________________

City ___________________________________________________________State/Province _____________________________________________

ZIP/Postal Code ____________________________________Country ________________________________________________________________

Phone _______________________________ Fax _______________________________ Email ___________________________________________

Geographic Region ❑ NW ❑ NE ❑ MW ❑ SW ❑ SE ❑ International

Student ❑ Yes ❑ No

AREAS OF INTEREST (select up to three)

❑ Teaching ❑ Social Sciences ❑ Biometrics/Health Sciences ❑ Computing Sciences ❑ Mathematical Sciences ❑ Business/Economics/Management Sciences ❑ Survey Research Methods ❑ Physical/Engineering

TYPE OF ORGANIZATION PREFERRED (select all that apply)

❑ Academic ❑ Government ❑ Industry ❑ Recruiter

INTERVIEWS ❑ Will attend Career Placement Service (JSM registration required) ❑ Will NOT attend (employers should contact me directly)

EDUCATION ❑ Bachelor’s ❑ Master’s ❑ Doctoral Candidate (Expected Completion Date ______________) ❑ Doctorate

CITIZENSHIP (select only one) ❑ U.S. Citizen ❑ Permanent Resident ❑ Nonresident, If nonresident, what Visa type? ____________________________________

AVAILABILITY ❑ Immediately ❑ <6 Months ❑ >6 Months

WORK EXPERIENCE ❑ Entry Level ❑ 1–3 years ❑ 4–6 years ❑ 7–9 years ❑ 10+ years

TRAVEL PREFERENCE ❑ No Travel ❑ Some Travel ❑ Frequent Travel

COMPUTER PROGRAMING ❑ ForTran ❑ C/C++ ❑ SQL ❑ Visual Basic ❑ Minitab ❑ JMP

STATISTICAL SOFTWARE ❑ SAS® ❑ SPSS® ❑ MatLab ❑ S-Plus/R®

CURRENT POSITION

Current Employer __________________________________________________________________________________________________________

Current Position Title ___________________________________________________Starting Date ________________Salary _____________________

Description of position ______________________________________________________________________________________________________

________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________

SPECIALIZED EXPERIENCE, SKILLS, ETC.________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________

________________________________________________________________________________________________________________________

Register by July 12, 2007, for discounted fees and to be included in Advance Online Applicant Access, available to employers prior to the meeting. Mail-in registrations MUST be postmarked by July 12, 2007. FAXES of this form are NOT accepted. Mail your completed form with your résumé, or register at www amstat.org/meetings/jsm/2007/placement.

Early Bird—May 1–June 21, 2007Early Bird fees are in effect until 11:59 p.m. EDT on June 21, 2007. Early Bird registrants will receive name badge(s) and func-tion tickets by mail prior to the conference. Bring these with you to avoid waiting in long registration lines. We will provide additional materials onsite.*

Advance Registration—June 22–July 12, 2007Advance registration fees are in effect until 11:59 p.m. EDT on July 12, 2007. Advance registrants receive confirmation only in advance. Come to the registration desk at the Salt Palace Convention Center to pick up all registration materials.

After July 12, 2007Register onsite July 28–August 2, 2007, at the Salt Palace Convention Center.

JSM Registration FeesFees include the program book, abstract book or CD-ROM, Opening Mixer, and Informal Dance Party. A copy of the 2007 Proceedings CD-ROM (to ship in early 2008) also is included, except where noted ✦.ASA reserves the right to adjust MEMBER registration types to the NONMEMBER type and to charge the difference in rates if stated membership is not currently active. In such event, you will first be notified and given an opportunity to update your ASA membership.

✖ Includes discounted first-year ASA dues; not available to renewing or recently lapsed members.

PaymentPayment must accompany registration. If you are paying by check, you must register by mail. If you are paying by credit card, you may register using any of the options listed. We are unable to accept purchase orders. Do not submit registration materials more than once. Make your check or money order payable to the American Statistical Association in U.S. funds drawn on a U.S. bank. The ASA Federal ID is #53-020-4661.

Preregistered Attendees via Abstract SubmissionIf you preregistered with an abstract submission and are adding functions to your registration, check the box “Preregistered with Abstract Submission” on the Registration Form. Name badge(s) and function tickets will be mailed to you prior to the conference.

Onsite RegistrationThe registration desk will be in the South Foyer of the Salt Palace Convention Center and open the following hours:

Saturday, July 28 Tuesday, July 31 7:00 a.m.–6:00 p.m. 7:30 a.m.–4:30 p.m.

Sunday, July 29 Wednesday, August 1 7:00 a.m.–8:30 p.m. 7:30 a.m.–4:30 p.m.

Monday, July 30 Thursday, August 2 7:30 a.m.–6:00 p.m. 7:30 a.m.–10:30 a.m.

Program and Abstracts OnlineThe preliminary program and abstracts will be available at www.amstat.org/meetings/jsm/2007/onlineprogram by March 26, 2007; the final program will be available online by July 9, 2007. The printed program book and your choice of abstract book or CD-ROM will be dis-tributed with registration materials in Salt Lake City.

Three ways to register... Online www.amstat.org/meetings/jsm/2007/onlinereg Fax (301) 206-9789 Mail JSM Registration P.O. Box 221 Annapolis Junction, MD 20701

Early Bird May 1–June 21

AdvanceJune 22–July 12

OnsiteJuly 28–August 2

Member $275 $305 $335

New ASA Member ✖ $350 $380 $410

Nonmember $390 $420 $455

Student Member $50 $50 $50

K–12 Teacher ✦ $70 $70 $70

Senior Member (Retired or over age 65) $85 $85 $85

One-day (Onsite Only) N/A N/A $235

Guest $20 $20 $20

Registration Information

Note: Career Placement Service forms should be sent separately to the address indicated on those forms.

Cancellations/Substitutions/RefundsPrepaid registrations submitted with abstracts

are nonrefundable.

All cancellations and substitutions must be submitted in writ-ing: Email: [email protected]; Fax: (301) 206-9789; Mail: JSM Registration, P.O. Box 221, Annapolis Junction, MD 20701.

• Cancellations received by 11:59 p.m. EDT on June 21, 2007: Cancellation fees are 20% of each item cancelled.

• Cancellations received by 11:59 p.m. EDT on July 12, 2007: Cancellation fees are 40% of each item cancelled.

• Cancellations received after 11:59 p.m. EDT on July 12, 2007, will not be refunded.

For questions or assistance, email [email protected] or call (866) 421-7169.

Registrations Not Accepted by Telephone or Email

Registration confirmations will be emailed to ALL preregistered attendees. Confirmations will be faxed or mailed by request only.

You can expect delays due to heavy volume during the weeks of registration deadlines.

* Please provide an accurate address on your registration form. The ASA is not responsible for lost, misdirected, incomplete, damaged, or late mail.

ROUNDTABLES with COFFEE$12 each; includes refreshmentsIndicate your fi rst and second choices by marking 1 or 2.

MONDAY TUESDAY WEDNESDAY July 30 July 31 August 1 ML01 _____ TL01 _____ WL01 _____ ML02 _____ TL02 _____ WL02 _____ ML03 _____ TL03 _____ WL03 _____ ML04 _____ TL04 _____ WL04 _____ ML05 _____ TL05 _____ WL05 _____ ML06 _____ TL06 _____ WL06 _____ ML07 _____ TL07 _____ WL07 _____ ML08 _____ TL08 _____ WL08 _____

TOTAL COFFEE COST $______

ROUNDTABLES with LUNCH$40 each; includes mealIndicate your fi rst and second choices by marking 1 or 2.

MONDAY TUESDAY WEDNESDAY July 30 July 31 August 1

EARLY BIRD & ADVANCE REGISTRATION FORM

Last/Family Name First/Given Name Middle Initial Badge Name (if different from First Name)

Membership(s): (check all that apply) ❑ ASA ❑ IMS ❑ SSC ❑ ENAR ❑ WNAR ASA ID# (if known) ___________________________________________

Title Organization

Address

City State/Province ZIP/Postal Code Country (Non-U.S.)

Phone Fax Email

In case of emergency at the meeting, list the name and phone number of the person we should contact. (Remains confi dential and is used only in case of emergency.)

Emergency Contact’s Name ____________________________________ Relationship to Registrant _______________________________ Telephone Number ______________________________

PLEASE TYPE OR PRINT CLEARLYCREDIT CARD OR CHECK PAYMENT INFORMATION(NOTE: We are unable to accept purchase orders as payment.)

❑ Check or money order enclosed payable to American Statistical Association (U.S. funds on a U.S. Bank)

Credit Card ❑ VISA ❑ MasterCard ❑ Amex

Card Number

/ Exp. Date CVS # (3-digit # on reverse of card)

Name of Cardholder


Member Nonmember Student

Saturday, July 28 CE_ 01C ❑ $575 ❑ $700 ❑ $340 CE_ 02C ❑ $340 ❑ $435 ❑ $200 CE_ 03C ❑ $340 ❑ $435 ❑ $200 CE_ 04C ❑ $340 ❑ $435 ❑ $200 CE_ 05C ❑ $340 ❑ $435 ❑ $200 CE_ 06C ❑ $340 ❑ $435 ❑ $200 CE_ 07C ❑ $340 ❑ $435 ❑ $200

Sunday, July 29 CE_ 08C ❑ $210 ❑ $275 ❑ $125 CE_ 09C ❑ $340 ❑ $435 ❑ $200 CE_ 10C ❑ $340 ❑ $435 ❑ $200 CE_ 11C ❑ $340 ❑ $435 ❑ $200 CE_ 12C ❑ $340 ❑ $435 ❑ $200 CE_ 13C ❑ $340 ❑ $435 ❑ $200 CE_ 14C ❑ $210 ❑ $275 ❑ $125

Monday, July 30 CE_ 15C ❑ $210 ❑ $275 ❑ $125 CE_ 16C ❑ $340 ❑ $435 ❑ $200 CE_ 17C ❑ $340 ❑ $435 ❑ $200 CE_ 18C ❑ $340 ❑ $435 ❑ $200 CE_ 19C ❑ $340 ❑ $435 ❑ $200 CE_ 20C ❑ $340 ❑ $435 ❑ $200 CE_ 21C ❑ $210 ❑ $275 ❑ $125

Tuesday, July 31 CE_ 22C ❑ $210 ❑ $275 ❑ $125 CE_ 23C ❑ $340 ❑ $435 ❑ $200 CE_ 24C ❑ $340 ❑ $435 ❑ $200 CE_ 25C ❑ $340 ❑ $435 ❑ $200 CE_ 26C ❑ $340 ❑ $435 ❑ $200 CE_ 27C ❑ $340 ❑ $435 ❑ $200 CE_ 28C ❑ $210 ❑ $275 ❑ $125

Wednesday, August 1Computer Technology Workshops $50 each

CE_ 29T ❑ CE_ 33T ❑ CE_ 37T ❑ CE_ 30T ❑ CE_ 34T ❑ CE_ 38T ❑ CE_ 31T ❑ CE_ 35T ❑ CE_ 39T ❑ CE_ 32T ❑ CE_ 36T ❑ CE_ 40T ❑

TOTAL CE COST $______

GUEST BADGESEnter names below. Fee includes Sunday Mixer, Tuesday Dance Party, and entrance into Exhibit Hall.

_______________________________@ $20 = $ _______Guest Name

_______________________________@ $20 = $ _______Guest Name

_______________________________@ $20 = $ _______Guest Name

TOTAL GUEST BADGE COST $______

Check all that apply:❑ I am a fi rst-time JSM attendee and ❑ will/ ❑ will not attend First-Time Attendee Reception (p.32) ❑ Please update my ASA customer information with this contact information.❑ I have a disability that requires special services (attach a statement of your needs). ❑ Please exclude my information from contact lists managed by JSM for use by outside entities.

TOURS

TOTAL TOUR COST $______

MEETING REGISTRATION FEES(mark the appropriate box)

Early Bird Advance May 1–June 21 June 22–July 12 Member ❑ $275 ❑ $305 New ASA Member ❑ $350 ❑ $380 Nonmember ❑ $390 ❑ $420 Student Member ❑ $ 50 ❑ $ 50 K–12 Teacher ❑ $ 70 ❑ $ 70 Senior Member ❑ $ 85 ❑ $ 85

Preregistered with Abstract Submission ❑ $ 0

MEETING REGISTRATION FEE $______*see Page 62 for cancellation policy ADD-ONS

TOTAL CE Cost $_______

TOTAL Guest Badge Cost $_______

TOTAL Coffee Cost $_______

TOTAL Lunch Cost $_______

TOTAL Tour Cost $_______

TOTAL REGISTRATION + ADD-ONS $_______

Quantity Price TotalSaturday, July 28 TR01_______ x $10.25 = $______ TR02_______ x $23.00 = $______Sunday, July 29 TR03_______ x $59.00 = $______ TR04_______ x $20.00 = $______Monday, July 30 TR05_______ x $20.00 = $______ TR06_______ x $27.00 = $______

Quantity Price TotalTuesday, July 31 TR07_______ x $40.00 = $______ TR08(Adult)____ x $11.00 = $______ TR08(Child)____ x $0.00 = $______ TR09_______ x $20.00 = $______Wednesday, August 1 TR10_______ x $33.00 = $______ TR11_______ x $27.00 = $______ TR12_______ x $40.00 = $______Thursday, August 1 TR13_______ x $59.00 = $______

ML09 _____ TL09 _____ WL09 _____ ML10 _____ TL10 _____ WL10 _____ ML11 _____ TL11 _____ WL11 _____ ML12 _____ TL12 _____ WL12 _____ ML13 _____ TL13 _____ WL13 _____ ML14 _____ TL14 _____ WL14 _____ ML15 _____ TL15 _____ WL15 _____ ML16 _____ TL16 _____ WL16 _____ ML17 _____ TL17 _____ WL17 _____ ML18 _____ TL18 _____ WL18 _____ ML19 _____ TL19 _____ WL19 _____ ML20 _____ TL20 _____ WL20 _____ ML21 _____ TL21 _____ WL21 _____ ML22 _____ TL22 _____ WL22 _____ ML23 _____ TL23 _____ WL23 _____ ML24 _____ TL24 _____ WL24 _____ ML25 _____ TL25 _____ WL25 _____ ML26 _____ TL26 _____ WL26 _____ ML27 _____ TL27 _____ WL27 _____ ML28 _____ TL28 _____ WL28 _____ ML29 _____ TL29 _____ WL29 _____ ML30 _____ TL30 _____ WL30 _____

❑ HEART HEALTHY ❑ KOSHER ❑ VEGETARIAN

TOTAL LUNCH COST $______

CONTINUING EDUCATION

ADD-ON FEES (mark the appropriate box)

ONLINE2007 PROGRAM

The Preliminary program will NOT appear in the May issue of Amstat News, but will be available online at http://www.amstat.org/meetings/jsm/2007/OnlineProgram

starting on March 26, 2007.

New This Year Starting May 1, 2007, you will be able to download or print a PDF version of the program. This preliminary program will be updated weekly until the final program is posted on July 9, 2007. When you arrive in Salt Lake City, Utah, make sure to refer to the final program and the program errata sheet or check the online program on the web site for a current version.

The FULL program for JSM 2007 is at

www.amstat.org/meetings/jsm/2007.

PresortedFirst Class MailU.S. Postage

PAIDPermit #361Alexandria, VA

American Statistical Association732 North Washington StreetAlexandria, VA 22314-1943 USA

REGISTER The FULL program for JSM 2007 is at www.amstat.org/meetings/jsm/2007. Online

JSM

STA

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ICS: H

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g the Power of Information

Salt Lake City, Utah July 29 to August 2, 2007

registration book07 · find out what your association is doing! come to the open meeting, meet your...

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