Selection Models for Nonignorable Missing Data
Published on 3. February 2005
Book
Paperback/Softback
128 pages
978-3-631-53499-1 (ISBN)
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.
More details
Series
Thesis
Doctoral thesis
2004
Language
English
Place of publication
Frankfurt a.M.
Germany
Target group
Professional and scholarly
Edition type
New edition
Illustrations
graphs
Dimensions
Height: 21 cm
Width: 14.8 cm
Weight
190 gr
ISBN-13
978-3-631-53499-1 (9783631534991)
Schweitzer Classification
Person
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.
Content
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.