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Statistics

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Collaborative Research: Multilevel Regression and Poststratification: A Unified Framework for Survey Weighted Inference

This research project will develop a unified framework for survey weighting through novel modifications of multilevel regression and poststratification (MRP) to incorporate design-based information into modeling. Real-life survey data often are unrepresentative due to selection bias and nonresponse. Existing methods for adjusting for known differences between the sample and population from which the sample is drawn have some advantages but also practical limitations.

Yang Feng

Associate Professor of Statistics

Andrew Gelman

Higgins Professor of Statistics and Professor of Political Science

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