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Activity Number: 613
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
Sponsor: Survey Research Methods Section
Abstract #319848 View Presentation
Title: A Calibrated Bayesian Method for Propensity Score Estimation
Author(s): Hejian Sang* and Jae-kwang Kim
Companies: Iowa State University and Iowa State University
Keywords: Nonresponse ; propensity score ; Bayesian approach ; ignorable ; nonignorable
Abstract:

Decreasing response rates in sample surveys is a serious problem and nonresponse weight adjustment using propensity score method is commonly adopted to compensate for unit nonresponse. However, the inference after nonresponse weight adjustment is complicated because the effect of estimating propensity score method needs to be incorporated. In this paper, we develop a new Bayesian approach to handling unit nonresponse under a parametric model for the response probabilities. The proposed Bayesian method is calibrated to frequentist inference. The computation does not involve Taylor linearization. Our proposed method is applicable to both ignorable and nonignorable response mechanism. Some asymptotic properties are established and the results from two simulation studies are presented.


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