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Biostatistics 3:245-265 (2002)
© 2002 Oxford University Press

Strategies to fit pattern-mixture models

Herbert Thijs, Geert Molenberghs, Bart Michiels, Geert Verbeke and Desmond Curran

Herbert Thijs, Geert Molenberghs. Biostatistics, Center for Statistics, Limburgs Universitair Centrum, Universitaire Campus, B-3590 Diepenbeek, Belgium geert.molenberghs{at}luc.ac.be
Bart Michiels. Janssen Research Foundation, Beerse, Belgium
Geert Verbeke. Biostatistical Centre, School of Public Health, Katholieke Universiteit Leuven, Capucijnenvoer 35, B-3000 Leuven, Belgium
Desmond Curran. EORTC Data Center, Brussels, Belgium

Whereas most models for incomplete longitudinal data are formulated within the selection model framework, pattern-mixture models have gained considerable interest in recent years (Little, 1993, 1994). In this paper, we outline several strategies to fit pattern-mixture models, including the so-called identifying restrictions strategy. Multiple imputation is used to apply this strategy to realistic settings, such as quality-of-life data from a longitudinal study on metastatic breast cancer patients.

Keywords: Delta method; Linear mixed model; Missing data; Repeated measures; Sensitivity analysis


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