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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/354

Title: Selection models and pattern-mixture models for incomplete categorical data with covariates
Authors: Michiels, Bart
Molenberghs, Geert
Lipsitz, Stuart R.
Keywords: Categorical data
Clustered data
Missing data
Longitudinal data
Issue Date: 1999
Citation: Biometrics, 55(3). p. 978-983
Abstract: Most models for incomplete data are formulated within the selection model framework. This paper studies similarities and differences of modeling incomplete data within both selection and pattern-mixture settings. The focus is on missing at random mechanisms and on categorical data. Point and interval estimation is discussed. A comparison of both approaches is done on side effects in a psychiatric study.
URI: http://hdl.handle.net/1942/354
DOI: 10.1111/j.0006-341X.1999.00978.x
ISI #: 000082683000047
ISSN: 0006-341X
Type: Journal Contribution
Validation: ecoom, 2000
Appears in Collections: Research publications

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