Abstract

Selection models and pattern-mixture models to analyze longitudinal quality of life data subject to dropout

Michiels, B., Molenberghs, G., Bijnens, L., Vangeneugden, T., and Thijs, H.

Longitudinally observed quality of life data with large amounts of dropout are analyzed. 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 dropout mechanisms. Since selection models and pattern-mixture models are based upon different factorizations of the joint distribution of measurement and dropout mechanisms, comparing both models concerning, for example, treatment effect, is a useful form of a sensitivity analysis.

  Last update: January, 24, 2003  - Contact : S. Malali