Selection models for nonignorable missing data
Author(s)
Bibliographic Information
Selection models for nonignorable missing data
（Anwendungsorientierte Statistik, Bd. 8）
P. Lang, 2005
- : us
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Note
Includes bibliographical references
Originally presented as the author's thesis (doctoral) -- Ludwig-Maximilians-Universität München, 2004
Description and Table of Contents
Description
An introduction to missing data in statistical applications is given in the beginning. The main part of the book deals with selection models for nonignorable missing data. The theory of selection models is described and illustrated by examples. Maximum Likelihood as well as Bayesian estimation approaches are discussed. A selection model with a nonparametric missing model that allows to treat flexible missing patterns is developed. This approach is unique in literature. The proposed model is extended to a model for longitudinal data.
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