Random-Effects Mixture, Shared-Parameter, and Selection Models

In this chapter, we examine three more models for nonignorable missing data. They represent a small subset of all those that have been proposed. However, these three models clearly illustrate the following:

1. All models for nonignorable data require the analyst to make strong assumptions.