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Sensitivity analysis of longitudinal binary quality of life data with drop‐out: an example using the EORTC QLQ‐C30
Author(s) -
Van Steen Kristel,
Curran Desmond,
Molenberghs Geert
Publication year - 2001
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1081
Subject(s) - categorical variable , generalized estimating equation , marginal model , gee , covariate , statistics , missing data , estimating equations , attrition , binary data , quality of life (healthcare) , longitudinal data , mathematics , econometrics , binary number , computer science , maximum likelihood , medicine , regression analysis , data mining , arithmetic , dentistry , nursing
Abstract Analysing quality of life data (QOL) may be complicated for several reasons. Quality of life data not only involves repeated measures but is also usually collected on ordered categorical responses. In addition, it is evident that not all patients provide the same number of assessments, due to attrition caused by death or other medical reasons. In the recent statistical literature, increasing attention is given to methods which can handle non‐continuous outcomes in the presence of missing data. The aim of this paper is to investigate the effect on statistical conclusions of applying different modelling techniques to QOL data generated from an EORTC phase III trial. Treatment effects and treatment differences are of major concern. First, a random‐effects model is fitted, relating a binary longitudinal response (derived from the physical functioning scale of the QLQ‐C30) to several covariates. In a second approach, marginal models are fitted, retaining the response variable and the mean structure used before. The fitted marginal models only differ with respect to the considered estimation procedure: generalized estimating equations (GEE); weighted generalized estimating equations (WGEE), and maximum likelihood (ML). Copyright © 2001 John Wiley & Sons, Ltd.