VISIT US AT http://surveys.virginia.edu

Thomas M.Guterbock,1 James M. Ellis,1 Deborah L. Rexrode,1 Casey M. Eggleston,1

Darrick Hamilton,2 & William A. Darity, Jr.3

Driven to Adapt: An Application of Adaptive Design with Multiple Low-productivity Telephone Samples

AAPOR Annual Conference – Anaheim, CA – May 15, 2014Adaptations

As the study progressed, we had to adapt:• Sampling methods and screening criteria

• More use of surname lists• More specific ethnic screening• Tighter geographic targeting

• Calling lab management• Don’t use all stations at once• Better feedback to interviewers• Outsource for better time zone and language

capabilities• Programming

• New screener logic facilitates changes• Production monitoring

• Change from overlapping counts to mutually exclusive categories

• New ways to acquire paradata from CATI system

• Used paradata to manage 30+ studies

Racial dot map of DC

Lorenz curves for ethnic distribution

NASCC is supported by grants from The Ford Foundation and the Federal Reserve Bank of Boston.

Author affiliations: 1) Center for Survey Research, University of Virginia. 2) Milano School of International Affairs, Management and Public Policy, The New School. 3) Research Network on Racial & Ethnic Inequality, Duke University.

SPECIFICITY (Targeted group as percent of completes)

High90-100%

Medium50-89%

Low10-49%

High.30-.60 Screened DC Asian

Surname Outsourced LA Chinese

Surname

Outsourced LA Filipino Surname Screened Tulsa American Indian

Surname Screened Miami Black Listed Unscreened DC African Surname Screened LA Black Listed

Unscreened DC Vietnamese and Korean Listed

Unscreened DC Black Listed Unscreened LA Black Listed Screened DC Black Listed

Medium

.20-.29

Outsourced LA Japanese Surname

Outsourced LA Hispanic Surname

Screened DC Hispanic Surname

Screened Tulsa Black and Latino Cell Phones

Unscreened DC Black Cell Phones

Unscreened Miami Black Cell Phones

Unscreened LA African Surname Screened Tulsa Black and Latino

Listed Screened LA Asian Surname Screened Tulsa Hispanic Surname Boston Dominican Listed

Boston Puerto Rican Listed Unscreened Miami Black

Listed

Low.00-.19 Screened Miami Hispanic

Surname Outsourced LA Vietnamese

Surname Outsourced LA Korean

Surname

Boston Black and Latino Cell Phones

Boston Hispanic Surname Boston Portuguese Surname Boston Black and Latino Listed Unscreened LA Asian Surname Screened LA Hispanic Surname

Boston Cape Verdean Listed Boston Caribbean Listed Boston Haitian Listed Screened DC Hispanic Cell

Phones Unscreened LA Black Cell

Phones

PR

OD

UC

TIV

ITY

(C

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s p

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Result: A Unique Dataset

Census tract and ZIP code data from 2010 ACS were used to determine if each group was sufficiently concentrated for geographic targeting. Lorenz curves represent incidence and coverage graphically.

Sampling Approach

Geographic Targeting

Main Group SubgroupUnique

Household Count

Multiple Response

CountAsian Vietnamese 157 168  Korean 107 111  Chinese 110 122  Japanese 75 78  Filipino 55 58  East Indians 104 109  Other Asian 73 93

Total Asian 681 739Latino Mexican 179 199  Central American 69 75  South American 110 118  Cuban 116 134  Puerto Rican 110 127  Dominican 55 56  Other Latino 78 101

Total Latino 717 810Black US Origin 461 543  Haitian/Caribbean 174 183  African Immigrant 120 129

Total Black 755 855Native American

Total Native American

237 248

Whites Total White 346 1046GRAND TOTAL   2736 3698

Note: Total household count =2,746; 10 cases were not assigned a final ethnicity.

The StudyThe National Asset Scorecard for Communities of Color [NASCC] is a detailed telephone survey designed to better understand the asset and debt positions of various ethnic and racial groups whose wealth status is often overlooked or inadequately measured.

NASCC by the Numbers

448,000 dialing attempts

87,000 numbers dialed70,000 advance letters

12,000 interviewer hours

31 distinct studies4.4 interviewer

hrs./comp.39 minutes long

2,746 completions

This group was not concentrated enough to target geographically.

Selecting these ZIP codes should yield 50% incidence and include 80% of all blacks in DC.

White Black Latino Asian