Dados Bibliográficos

AUTOR(ES) S. Lee , Richard Valliant
AFILIAÇÃO(ÕES) University of California, Los Angeles, University of Michigan, Ann Arbor
ANO 2009
TIPO Artigo
PERIÓDICO Sociological Methods and Research
ISSN 0049-1241
E-ISSN 1552-8294
EDITORA Annual Reviews (United States)
DOI 10.1177/0049124108329643
CITAÇÕES 5
ADICIONADO EM 2025-08-18
MD5 93cc86d1aa36bfa07d0dada58da3f059

Resumo

A combination of propensity score and calibration adjustment is shown to reduce bias in volunteer panel Web surveys. In this combination, the design weights are adjusted by propensity scores to correct for selection bias due to nonrandomized sampling. These adjusted weights are then calibrated to control totals for the target population and correct for coverage bias. The final set of weights is comprised of multiple components, and the estimator of a total no longer takes a linear form. Therefore, approximate methods are needed to derive variance estimates. This study compares three variance estimation methods through simulation. The first method resembles what is used in commercial statistical software based on squared residuals. The second approach uses a variance estimator originally derived for the generalized regression estimator. The third method uses jackknife replication. Results indicate bias reduction is crucial for valid variance estimation and favor the replication method over the other approaches.

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