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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/401

Title: Analysing longitudinal continuous quality of life data with dropout
Authors: Curran, Desmond
Molenberghs, Geert
Aaronson, N.
Fossa, S.
Sylvester, Richard
Keywords: Missing data
Clinical trials
Longitudinal data
Issue Date: 2002
Publisher: ARNOLD
Citation: Statistical Methods in Medical Research, 11(1). p. 5-23
Abstract: Quality of Life (QL) is becoming an increasingly popular endpoint in phase III cancer clinical trials. However, there is still no agreement as to what is the optimal approach to analysis. In this paper we review some concepts which should be considered during a QL analysis. We present two modelling approaches that have been substantively developed in other research fields: selection models and pattern-mixture models. These models are compared using data from an EORTC clinical trial in poor-prognosis prostate cancer patients. It is illustrated that, although selection models and pattern mixture are probabilistically equivalent, they may shed completely different light on data from a modeller's point of view.
URI: http://hdl.handle.net/1942/401
DOI: 10.1191/0962280202sm270ra
ISI #: 000174362000002
ISSN: 0962-2802
Category: A1
Type: Journal Contribution
Validation: ecoom, 2003
Appears in Collections: Research publications

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