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Department seminar by Zhiqiang Tan, Rutgers UniversityExport this event to calendar

Friday, October 26, 2012 — 2:00 PM EDT

"Missing data problems and survey sampling"

Consider estimating the mean of an outcome in the presence of missing data or estimating population average treatment effects in causal inference. A doubly robust estimator remains consistent if an outcome regression model or a propensity score model is correctly specified. In this talk, we present developments of estimators which are not only doubly robust but also, in a certain sense, efficient and stable, from the perspectives of estimating equations and nonparametric likelihoods. Furthermore, we discuss how such developments have interesting connections to calibration estimation in survey sampling, and demonstrate that this approach leads to design-efficient calibration estimators for rejective and high-entropy sampling.

Location 
M3 - Mathematics 3
3127
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

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