This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 639
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Survey Research Methods
Abstract - #307944
Title: Some Theory for the Propensity Scoring Adjustment Estimator
Author(s): Jae-Kwang Kim+ and Minsun Kim* and Jay Breidt
Companies: Iowa State University and Iowa State University and Colorado State University
Address: Snedecor Hall, Ames, IA, 50011,
Keywords: Calibration ; Missing data ; Nonresponse weighting adjustment ; Undercoverage ; Unit nonresponse

The method of propensity scoring adjustment is commonly used to handle selection bias in many applications, including unit nonresponse and undercoverage in sample surveys. The propensity score is computed using auxiliary variables observed throughout the sample. We discuss some asymptotic properties of the propensity score adjustment estimator and derive an optimal propensity score estimator. The proposed optimal estimator is closely related with the prediction estimator based on an unconditional exponential tilting model. Variance estimation is discussed and the results from two simulation studies are presented.

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