leuvenstatiq a new start geert molenberghsadvances in statistical methods for the health sciences:...

LeuvenStatIQ

A New Start

Geert Molenberghs

Leuven Statistics Day, May 28, 2010

Katholieke Universiteit Leuven, Belgium

[email protected]

www.kuleuven.ac.be/biostat/

Goal, Planning, Consultancy

Timing Activity

1 November 2009 Change chairmanship

Fall/Winter/Spring 2009–2010 Consultancy

Turn 2009–2010 Preliminary Report College van Bestuur

January–February 2010 Preparation dry run

March–April 2010 Start dry run

Leuven Statistics Day Reporting

1 August 2010 Start new structure

Groep Humane Wetenschappen, 6 mei 2010 1

LeuvenStatIQ∗

“LeuvenStat wenst een leidinggevend engerenommeerd academisch centrum voor alledomeinen van de statistiek te zijn, binnen de

K.U.Leuven, Vlaanderen, Belgie, Europa en dewereld. LeuvenStat is toegewijd aan hoogwaardig

wetenschappelijk onderzoek, academischonderwijs, contractonderzoek en

wetenschappelijke dienstverlening ensamenwerking in de statistiek.”

∗ International Quality


LeuvenStatIQ∗

“LeuvenStat is a leading and reputable academiccenter for all areas of statistics, within

K.U.Leuven, Flanders, Belgium, Europe, andglobally. LeuvenStat is dedicated to high quality

scientific research, academic education,consulting and scientific collaboration in

statistics.”∗ International Quality


Full Interaction

Research Education

Scientific Collaboration / Consulting

. Quality

. International


Research

Current Position

• Strong research tradition in various areas

• We have top researchers

• Strong fundamental & strong applied traditions

• Leuven Statistics Days

• Leuven Statistics Book Library (LeuvenStatBooks)

• LStat research = very strong union of all participating groups


LeuvenStatBooks

Aerts, M., Geys, H., Molenberghs, G., and Ryan, L. (2002). Topics in Modelling of Clustered Data. London:Chapman & Hall.

Auget, J.-L., Balakrishnan, N., Mesbah, M., and Molenberghs, G. (2007). Advances in Statistical Methods for theHealth Sciences: Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis.

New York: Birkhauser.

Beirlant, J., Goegebeur, Y., Segers, J., and Teugels, J. (2004). Statistics of Extremes: Theory and Applications. New

York: John Wiley & Sons.

Beirlant, J., Teugels, J.L., and Vynckier, P. (1996). Practical Analysis of Extreme Values. Coronet Books Inc.

Billiet, J. (1990). Methoden van Sociaal-Wetenschappelijk Onderzoek: Ontwerp en Dataverzameling. Leuven: Acco.

Billiet, J., Loosveldt, G., and Waterplas, L. (1984). Het Survey-Interview Onderzocht. Sociologische Studies enDocumenten. Leuven University Press.

Bultheel, A. and Cools, R. (2009). The Birth of Numerical Analysis. Singapore: World Scientific.

Burzykowski, T., Molenberghs, G., and Buyse, M. (2005). The Evaluation of Surrogate Endpoints. New York:

Springer.

Claeskens, G. and Hjort, N.L. (2008). Model Selection and Model Averaging. Cambrdige: Cambridge University Press.

De Boeck, P. and Wilson, M. (2004). Explanatory Item Response Models. A Generalized Linear and Nonlinear

Approach. New York: Springer.


Delwit, P., Rea, A., and Swyngedouw, M. (2007). Bruxelles Ville Ouverte. Immigration et Diversite Culturelle auCoeur de l’Europe. Paris: L’Harmattan.

Denuit, M., Dhaene, J., Goovaerts, M., and Kaas, R. (2005). Actuarial Theory for Dependent Risks—Measures,Orders and Models. New York: John Wiley & Sons.

Denuit, M., Dhaene, J., and Goovaerts, M. (2005). Actuarial Theory for Dependent Risks. John Wiley & Sons.

Delaigle, A. and Gijbels, I. (2008). Deconvolution, Measurement Errors and Applications. Cambridge: Cambridge

University Press.

Dhaene, G. (1997). Encompassing: Formulation, Properties and Testing. Lecture Notes in Economics andMathematical Systems. New York: Springer.

Dhaene, J., Kolev, N., and Morettin, P. (2003). Proceedings of the First Brazilian Conference on Statistical Modellingin Insurance and Finance. Institute of Mathematics and Statistics, University of Sao Paulo.

Dmitrienko, A., Molenberghs, G., Christy Chuang-Stein, J.L., and Offen, W.W. (2005). Analysis of Clinical Trial DataUsing SAS: A Practical Guide. Cary, NC: Sas Press.

Dmitrienko, A., Molenberghs, G., Christy Chuang-Stein, J.L., and Offen, W.W. (2009). Analysis of Clinical Trial DataUsing SAS: A Practical Guide. (Japanese Translation). Kodansya Scientific & SAS Press.

Dutter, R., Filzmoser, P., Gather, U., and Rousseeuw, P.J. (2002). Developments in Robust Statistics: InternationalConference on Robust Statistics 2001. Heidelberg: Physica-Verlag.

Edgington, E. and Onghena, P. (2007) Randomization Tests (Fourth edition). Boca Raton: Chapman Hall/CRC.

Fan, J., and Gijbels, I. (1996). Local Polynomial Modelling and Its Applications. New York: Chapman & Hall/CRC.


Fitzmaurice, G., Davidian, M., Molenberghs, G., and Verbeke, G. (2009). Longitudinal Data Analysis. Handbooks ofModern Statistical Methods. New York: Chapman & Hall/CRC.

Geeraerts, D., Speelman, D., and Grondelaers, S. (2009). Measuring Lexical Standardisation. Oxford: Oxford

University Press.

Goethals, J. and Pauwels, L. (2008). Kwantitatieve en Kwalitatieve Criminologische Onderzoeksmethodes: een

Introductie. Leuven: Acco.

Grondelaers, S. and Speelman, D. (2009). A psycho- and Corpuslinguistic Analysis of Existential Sentences: Modelling

Indefinite Reference Processing in Dutch. Cognitive linguistic research. Berlin–New York: Mouton de Gruyter.

Hampel, F., Ronchetti, E.M., Rousseeuw, P.J., and Stahel, W.A. (2005). Robust Statistics: The Approach Based on

Influence Functions. New York: John Wiley & Sons.

Hubert, M., Pison, G., Struyf, A., and Van Aelst, S. (2004). Theory and Applications of Recent Robust Methods.

Basel: Birkhauser.

Jansen, M. and Oonincx, P. (2005). Second Generation Wavelets and Applications. New York: Springer.

Jansen, M. (2001). Noise Reduction by Wavelet Thresholding. Lecture Notes in Statistics 161. New York: Springer.

Kaas, R., Goovaerts, M., Dhaene, J., and Denuit, M. (2003). Modern Actuarial Risk Theory. Dordrecht: KluwerAcademic Publishers.

Kaas, R., Goovaerts, M., Dhaene, J., and Denuit, M. (2005). Modern Actuarial Risk Theory (Chinese translation).

Bejing: Science Press.

Kaufman, L. and Rousseeuw, P.J. (2005). Finding Groups in Data: An Introduction to Cluster Analysis. New York:

John Wiley & Sons.


Kenis, L., Billiet, J., and Pasture, P. (2010). The Transformation of the Christian Churches in Western Europe1945-2000. (Kadoc Studies on Religion, Culture and Society 6). Leuven University Press.

Komarek, A., Bogaerts, K., and Lesaffre, E. (2009). Survival Analysis with Interval-Censored Data: A PracticalApproach with R, SAS and WinBUGS. London: Chapman & Hall/CRC.

Kyprianou, A., Schoutens, W., and Wimott, P. (2005). Exotic Option Pricing and Advanced Lvy Models. New York:John Wiley & Sons.

Lawson, A.B., Biggeri, A., Bohning, D., and Lesaffre, E. (2009). Disease Mapping and Risk Assessment for PublicHealth. New York: John Wiley & Sons.

Lesaffre, E., Feine, J., Leroux, B., and Declerck, D. (2009). Statistical and Methodological Aspects of Oral Health

Research. Chichester: John Wiley & Sons.

Loosveldt, G., Swyngedouw, M., and Cambre, B. (2007). Measuring Meaningful Data in Social Research.

Leuven/Voorburg: Acco.

Markovsky, I., Willems, J.C., Van Huffel, S., De Moor, B. (2006). Exact and Approximate Modeling of Linear

Systems: A Behavioral Approach. Monographs on Mathematical Modeling and Computation. Siam.

Molenberghs, G. and Kenward, M.G. (2007). Missing Data in Clinical Studies. New York: John Wiley.

Molenberghs, G. and Verbeke, G. (2005). Models for Discrete Longitudinal Data. New York: Springer.

Rousseeuw, P.J. and Leroy, A.M. (2003). Robust Regression and Outlier Detection. New York: John Wiley & Sons.

Schoutens, W. (2000). Stochastic Processes and Orthogonal Polynomials. Lecture Notes in Statistics. New York:

Springer.


Schoutens, W. (2003). Levy Processes in Finance: Pricing Financial Derivatives. New York: John Wiley & Sons.

Schoutens, W. and Cariboni, J. (2009). Levy Processes in Credit Risk. New York: John Wiley & Sons.

Stoop, I., Billiet, J., Koch, A., and Fitzgerald, R. (2010). Improving Survey Response: Lessons Learned from the

European Social Survey. New York: John Wiley & Sons.

Suykens, J., Horvath, G., Basu, S., Micchelli, C., and Vandewalle, J. (2003). Advances in Learning Theory : Methods,

Models and Applications. Amsterdam: IOS Press.

Van Gestel, T. and Baesens, B. (2009). Credit Risk Management: Basic Concepts: Financial Risk Components,

Rating Analysis, Models, Economic and Regulatory Capital. Oxford: Oxford University Press.

Van Huffel, S. and Lemmerling, P. (2002). Total Least Squares and Errors-in-Variables Modeling: Analysis,

Algorithms and Applications. New York: Springer.

Van Huffel, S. (1997). Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling.—Philadelphia: SIAM Proceedings.

Van Huffel, S. and Vandewalle, J. (1987). The Total Least Squares Problem: Computational Aspects and Analysis.

(Frontiers in Applied Mathematics). Siam.

Verbeke, G. and Molenberghs, G. (1997). Linear Mixed Models In Practice: A SAS Oriented Approach. Lecture Notesin Statistics 126. New York: Springer.

Verbeke, G. and Molenberghs, G. (2000). Linear Mixed Models for Longitudinal Data. New York: Springer.

Verbeke, G. and Molenberghs, G. (2001). Linear Mixed Models in Practice. A SAS Oriented Approach. Japanese

translation by Matsyama, Y., Yamaguchi, T., Springer GmbH & Co. KG through Japan UNI Agency, Inc. Tokyo,

320 pages.


Verbeke, G. and Molenberghs, G. (2009). Linear Mixed Models for Longitudinal Data (Paperback Edition). New York:Springer.

Verbeke, G., Molenberghs, G., Aerts, M., and Fieuws, S. (2003). 18th International Workshop on StatisticalModelling. Katholieke Universiteit Leuven.

Vervaeke, G., Vanderhallen, M., and Van Koppen, P. (2003). Much Ado About Crime: Chapters on Psychology andLaw. Brussel: Politeia.

Voye, L., Billiet, J., and Dobbelaere, K. (1999). Sociology and Religions/Sociologie Et Religions: An AmbiguousRelationship/Des Relations Ambigues. Kadoc-Studies, 23 (French Edition). Cornell University Press.


Aims

• Increasing international footprint

• Leuven Statistics Days (LSD): frequency, concept enlargement, international

• Contribution Leuven Doctoral Program in Statistics (LDPS)

. dialogue with Doctoral School: relevant activities for PhDs in statistics

. relevant activities for users of statistics

. PhD in statistics

• Fora, themes, research lines. Examples:

. Biometry / bioinformatics forum (group biomedical sciences, BIW, psychology,engineering,. . . )


Education

Present Situation

• Responsibility for Master in Statistics

• Broad range of educational activities, loosely structured

• Fragmented, related to K.U.Leuven’s structural complexity:

. Breadth: we come from various faculties

. Depth: many decision layers


Goals

• Bachelor (and master) education

. Wholesome vision ←− interaction with authorities / O.O.I.

•Master in Statistics

. administrative reorganization

. even clearer profiles

. interaction with short-course program and PhD training

• Erasmus Mundus

. Statistics / Actuarial sciences

. Biostatistics


• Leuven STATistics STATe of the art training initiative (L-STAT2).

. Internationally recognized short course-program

. Initial −→ forefront

. Cf. Lancaster, Edinburgh, Reading,. . .

. Our own strong themes deserve a place: model selection, robust statistics,forecasting in economy and business, fronteers in image analysis, longitudinaland incomplete data, mixed models/hierarchical data in psychometrics,biometry, and survey research, design of experiments, statisticalbioinformatics,. . .

. osmosis with three Doctoral Schools

. LeuvenStatBooks


Scientific Collaboration and Consulting

Present Situation

• Central & group-specific & sometimes collaborative

• Need for global vision

• Need for expansion of central facilities ←− hiring

• Need for dispatch


Goals

• fine-tuning central versus de-central consulting

• “subsidiarity”

• IOF

• spin off

• attracting resources from all four funding channels

• broad participation at all levels (professors, postdoc, predoc) in consulting


Administrative Structure

• Advice:

. Past Presidents

. International Advisory Board

. Board of Stakeholders


• Leadership Structure:

. Chair/Vice-chair G. Molenberghs / M. Vandebroek

Y. 1 Y. 2 Y. 3 Y. 4 Y. 5 Y. 6 Y. 7 Y. 8 Y. 9 Y. 10 Y. 11 Y. 12

VC2 C2 C2 VC2 VC4 C4 C4 VC4 VC6 C6 C6 VC6

C1 VC1 VC3 C3 C3 VC3 VC5 C5 C5 VC5 VC7 C7

∗ From two different groups

∗ No overlap with chairmanship of other committee

. Committee for Research I. Gijbels

. Committee for Education G. Molenberghs / M. Vandebroek

. Committee for Scientific Collaboration and Consulting A.-M. De Meyer

. =⇒ Board of Directors all five


. Steering Committee

∗ One ZAP member per faculty

∗ Basis for support

∗ Once per term

. General Assembly

∗ All ZAP members

∗ At annual meeting: information, brainstorm


leuvenstatiq a new start geert molenberghsadvances in statistical methods for the health sciences:...

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