Journal
STATISTICS IN MEDICINE
Volume 26, Issue 1, Pages 110-123Publisher
WILEY
DOI: 10.1002/sim.2458
Keywords
treatment effectiveness; propensity adjustment; longitudinal study; observational study; misspecification
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Funding
- NIMH NIH HHS [MH60447, MH68638] Funding Source: Medline
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A mixed-effects propensity adjustment is described that can reduce bias in longitudinal studies involving non-equivalent comparison groups. There are two stages in this data analytic strategy. First, a model of propensity for treatment intensity examines variables that distinguish among subjects who receive various ordered doses of treatment across time using mixed-effects ordinal logistic regression. Second, the effectiveness model examines multiple times until recurrence to compare the ordered doses using a mixed-effects grouped-time survival model. Effectiveness analyses are initially stratified by propensity quintile. Then the quintile-specific results are pooled, assuming that there is not a propensity x treatment interaction. A Monte Carlo simulation study compares bias reduction in fully specified propensity model relative to misspecified models. In addition, type I error rate and statistical power are examined. The approach is illustrated by applying it to a longitudinal, observational study of maintenance treatment of major depression. Copyright (c) 2005 John Wiley & Sons, Ltd.
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