Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/363

Title: A Pattern-Mixture Odds Ratio Model for Incomplete Categorical Data
Authors: Michiels, Bart
Molenberghs, Geert
Lipsitz, Stuart
Keywords: Categorical data
Missing data
Issue Date: 1999
Citation: Communications in Statistics: Theory and Methods, 28(12). p. 2843-2869
Abstract: Most models for incomplete data are formulated within the selection model framework. Pattern-mixture models are increasingly seen as a viable alternative, both from an interpretational as well as from a computational point of view (Little 1993, Hogan:and Laird 1997, Ekholm and Skinner 1998). Whereas most applications are either for continuous normally distributed data or for simplified categorical settings such as contingency tables, we show how a multivariate odds ratio model (Molenberghs and Lesaffre 1994, 1998) can be used to fit pattern-mixture models to repeated binary outcomes with continuous covariates. Apart from point estimation, useful methods-for interval estimation are presented and data from a clinical study are analyzed to illustrate the methods.
URI: http://hdl.handle.net/1942/363
DOI: 10.1080/03610929908832453
ISI #: 000084122200004
ISSN: 0361-0926
Type: Journal Contribution
Validation: ecoom, 2000
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
Published version778.95 kBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.