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Selection Models for Nonignorable Missing Data

by Sandro Scheid (Author)
©2005 Thesis 128 Pages

Summary

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.

Details

Pages
128
Year
2005
ISBN (Softcover)
9783631534991
Language
English
Keywords
Daten Selektionsmodell longitudinale Daten Statistik Wahrscheinlichkeit Fehlende Daten nichtparametrisches Fehlermodell
Published
Frankfurt am Main, Berlin, Bern, Bruxelles, New York, Oxford, Wien, 2005. 128 pp., num. graphs

Biographical notes

Sandro Scheid (Author)

The Author: Sandro Scheid was born in Munich 1969. After his studies of Economics at the University of Bremen and the Freie Universität of Berlin, between 1989 and 1993, the author gained a degree in Statistics at the Department of Statistics at the University of Munich in 2001. He worked with a research project of the German Scientific Foundation that deals with discrete structures. The author’s topic within this project was missing data. He finished his doctoral thesis in 2004.

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Title: Selection Models for Nonignorable Missing Data