Full Citation

Title: Alternative Variance Estimates in the Current Population Survey and American Community Survey

Citation Type: Conference Paper

Publication Year: 2011

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Abstract: The Current Population Survey (CPS) and American Community Survey (ACS) are based on complex samples. As such, variance and standard error estimates need to be adjusted. Assuming a simple random sample (SRS) (the default of most statistical packages) will result in biased standard errors and statistical tests of significance. We describe and evaluate alternative variance estimation methods that accommodate sample design complexity. Using successive difference replication (SDR) as a gold-standard we evaluate various alternatives including a Taylor series (TS) approach, Census Bureau variance parameters, and the SRS method. For most variables considered, in both surveys and across geographic domains, the TS preformed better than design factor method. These results show that analysts wishing to avoid the cumbersome computation of design factor based standard errors can use a Taylor Series approach based on publically available geographic variables.

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Authors: Graven, Peter; Boudreaux, Michel; Davern, Michael

Conference Name: Population Association of America

Publisher Location: Washington, D.C.

Data Collections: IPUMS USA, IPUMS CPS

Topics: Methodology and Data Collection, Other

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