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Selection Models for Nonignorable Missing Data

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Sandro Scheid

Contents: Introduction to missing data problems in general – Selection models for nonignorable missing data – Discussion of Maximum Likelihood and Bayesian estimation routines – Development of a selection model with a nonparametric missing model – Extension of the latter to a model for longitudinal data.