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CONFERENCE POSTER
Weighted Estimation for Analyses with Missing Data
Samii, Cyrus

Abstract
Missing data plague data analyses in political science. The recent applied statistics literature reflects renewed interest in weighting methods for missing data problems. Three properties are stressed in this literature: (i) robustness, (ii) the ability to use post-treatment information in causal analysis, and (iii) methods to gain efficiency. I present these results, hoping to show the potential in using refashioned weighting methods for political science research.

Keywords
doubly robust
inverse probability weighting
missing data
post-treatment
regression
sample selection
semi-parametric


File
icnPdfMini samiiweightspostertexsm.pdf


Uploaded
07-21-2010

Poster Category
Grad Students

Document ID Number
1226


   
wustlArtSci