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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/392

Title: Selection models and pattern-mixture models to analyze longitudinal quality of life data subject to dropout
Authors: Michiels, Bart
Molenberghs, Geert
Bijnens, Luc J.M.
Vangeneugden, Tony
Thijs, Herbert
Keywords: Clinical trials
Missing data
Longitudinal data
Issue Date: 2002
Publisher: JOHN WILEY
Citation: Statistics in Medicine, 21(8). p. 1023-1041
Abstract: Longitudinally observed quality of life data with large amounts of drop-out are analysed. First we used the selection modelling framework, frequently used with incomplete studies. An alternative method consists of using pattern-mixture models. These are also straightforward to implement, but result in a different set of parameters for the measurement and drop-out mechanisms. Since selection models and pattern-mixture models are based upon different factorizations of the joint distribution of measurement and drop-out mechanisms, comparing both models concerning, for example, treatment effect, is a useful form of a sensitivity analysis.
URI: http://hdl.handle.net/1942/392
Link to publication: https://lirias.kuleuven.be/bitstream/123456789/359934/3/93.pdf
DOI: 10.1002/sim.1064
ISI #: 000174753000001
ISSN: 0277-6715
Category: A1
Type: Journal Contribution
Validation: ecoom, 2003
Appears in Collections: Research publications

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