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Activity Number: 442 - State-Of-The-Art Inferential Approaches for Non-Probability Samples
Type: Invited
Date/Time: Wednesday, July 31, 2019 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #300269
Title: Sample Matching and Double Robust Estimation with Non-Probability Samples
Author(s): Changbao Wu*
Companies: University of Waterloo
Keywords: Probability samples; Non-probability samples; Statistical inference; Doubly robust ; Variance estimation

We provide an overview on recent developments for analyzing non-probability survey samples. Inferential frameworks and theoretical results on sample matching and double robust estimation are discussed, and finite sample performances of the estimators are examined through simulation studies. An application to analyzing a non-probability survey sample from the PEW Research Centre is presented. Some practical issues are also discussed.

Authors who are presenting talks have a * after their name.

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