#  Models for Missing Data 

 



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The lecture slides are [here](/file_url/496) and a handout for one-page-at-a-time (color) printing is [here](/file_url/496).

   ![Lecture 9](/sites/g/files/omnuum7421/files/styles/hwp_1_1__720x720_scale/public/gov2001/files/lecture_9.png?itok=t7UQr5Ju) 

 

"Models for Missing Data" covers the following topics:

1. Overview
2. Missingness Assumptions
3. Application Specific Methods
4. Multiple Imputation
5. Computational Algorithms
6. What Can Go Wrong
7. Time Series, Cross-Sectional Imputations