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Bayesian Data Analysis, Third Edition, 3rd Edition by Donald B. Rubin, Aki Vehtari, David B. Dunson, Hal S. Stern, John B. Carlin, Andrew Gelman

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Chapter 18

Models for missing data

Our discussions of probability models in previous chapters, with few exceptions, assume that the desired dataset is completely observed. In this chapter we consider probability models and Bayesian methods for problems with missing data. This chapter applies some of the terminology and notation of Chapter 8, which describes models for collection and observation of data.

We show how the analysis of problems involving missing data can often be separated into two main tasks: (1) multiple imputation—that is, simulating ...

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