The propensity score adjustment is a method to reduce bias in observational studies. We propose a strategy that involves a novel combination of three data analytic techniques, which adapts the propensity adjustment for additional perturbations of longitudinal, observational studies. First, ordinal logistic regression examines propensity for ordinal doses of treatment. Second, a mixed-model approach incorporates the multiple treatment trials and multiple episodes that are characteristic of chronically ill subjects. Finally, a mixed-effects grouped-time survival model incorporates the propensity score in treatment effectiveness analyses. The strategy that is applied here to an observational study of affective illness can also be used to evaluate the effectiveness of treatments for other chronic illnesses. Copyright © 2001 John Wiley & Sons, Ltd.