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Activity Number: 299
Type: Topic Contributed
Date/Time: Tuesday, August 11, 2015 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #315059 View Presentation
Title: Weighted Estimating Equations Based on Response Propensities in Terms of Covariates That Are Observed Only for Responders
Author(s): Eric Slud*
Companies: U.S. Census Bureau
Keywords: Survey weights ; Missing at Random ; Calibration ; Consistency ; Efficiency
Abstract:

Weighted estimating equations are frequently used to estimate parameters in surveys and randomized experiments in settings where there is missing data due to nonresponse. The weights are generally related to the reciprocals of the "propensities" or conditional probabilities of response for individual subjects in terms of subject-level covariates which are known or observed even for nonresponding subjects. The consistency properties for the resulting estimating equations depend crucially on the "Missing at Random" (MAR) property for outcome variables in terms of the covariates used to construct the weights. Yet the MAR property may hold only when propensities reflect covariates observable simultaneously with outcome-variable responses. This talk describes settings in which such propensities may be used to adjust for nonresponse, consistently and sometimes efficiently, when population-level information about the full set of covariates is known or estimated from external data sources. The methods will be illustrated using data from the American Community Survey.


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