Missing data is common in real-world data, but popular procedures for handling missing data may be difficult to use, only work for certain types of models, and/or produce biased estimates under certain conditions.
In this workshop, you will learn how to use Blimp, an easy-to-use program that uses Bayesian estimation for missing data.
Topics will include missing data mechanisms, an introduction to Bayesian statistics, model specification in Blimp, and assessing model fit and convergence. Ample time will be spent working on in-class exercises.
We will take a one-hour lunch break around noon.
Instructor: Struck
Room: 3218 Sewell Social Sciences Building
Date: 6/18
Time: 9:00 - 4:00
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