Longitudinal studies have a prominent role in psychiatric research; however, statistical methods for analyzing these data are rarely commensurate with the effort involved in their acquisition. Frequently the majority of data are discarded and a simple end-point analysis is performed. In other cases, so called repeated-measures analysis of variance procedures are used with little regard to their restrictive and often unrealistic assumptions and the effect of missing data on the statistical properties of their estimates. We explored the unique features of longitudinal psychiatric data from both statistical and conceptual perspectives. We used a family of statistical models termed random regression models that provide a more realistic approach to analysis of longitudinal psychiatric data. Random regression models provide solutions to commonly observed problems of missing data, serial correlation, time-varying covariates, and irregular measurement occasions, and they accommodate systematic person-specific deviations from the average time trend. Properties of these models were compared with traditional approaches at a conceptual level. The approach was then illustrated in a new analysis of the National Institute of Mental Health Treatment of Depression Collaborative Research Program dataset, which investigated two forms of psychotherapy, pharmacotherapy with clinical management, and a placebo with clinical management control. Results indicated that both person-specific effects and serial correlation play major roles in the longitudinal psychiatric response process. Ignoring either of these effects produces misleading estimates of uncertainty that form the basis of statistical tests of hypotheses.

In the NIMH Treatment of Depression Collaborative Research Program (TDCRP), 250 depressed outpatients were randomly assigned to interpersonal psychotherapy, cognitive-behavioral therapy, imipramine plus clinical management, or pill placebo plus clinical management treatments. Although all treatments demonstrated significant symptom reduction with few differences in general outcomes, an important question concerned possible effects specific to each treatment. The therapies differ in rationale and procedures, suggesting that mode-specific effects may differ among treatments, each of which was precisely specified, applied appropriately, and shown to be discriminable. Outcome measures were selected for presumed sensitivity to the different treatments. Findings provided only scattered and relatively insubstantial support for mode-specific differences. None of the therapies produced consistent effects on measures related to its theoretical origins.

This study reports on the relationship of therapist competence to the outcome of cognitive-behavioral treatment in the National Institute of Mental Health Treatment of Depression Collaborative Research Program. Outpatients suffering from major depressive disorder were treated by cognitive-behavioral therapists at each of 3 U.S. sites using a format of 20 sessions in 16 weeks. Findings provide some support for the relationship of therapist competence (as measured by the Cognitive Therapy Scale) to reduction of depressive symptomatology when controlling for therapist adherence and facilitative conditions. The results are, however, not as strong or consistent as expected. The component of competence that was most highly related to outcome is a factor that reflects the therapist's ability to structure the treatment.

Random regression models (RRMs) were used to investigate the role of initial severity in the outcome of 4 treatments (cognitive-behavior therapy [CBT], interpersonal psychotherapy [IPT], imipramine plus clinical management [IMI-CM], and placebo plus clinical management [PLA-CM]) for outpatients with major depressive disorder seen in the National Institute of Mental Health Treatment of Depression Collaborative Research Program. Initial severity of depression and impairment of functioning significantly predicted differential treatment effects. A larger number of differences than previously reported were found among the active treatments for the more severely ill patients; this was due, in large part, to the greater power of the present statistical analyses.

Objective: The authors investigated patient characteristics predictive of treatment response in the National Institute of Mental Health (NIMH) Treatment of Depression Collaborative Research Program. Method: Two hundred thirty-nine outpatients with major depressive disorder according to the Research Diagnostic Criteria entered a 16-week multicenter clinical trial and were randomly assigned to interpersonal psychotherapy, cognitive-behavior therapy, imipramine with clinical management, or placebo with clinical management. Pretreatment sociodemographic features, diagnosis, course of illness, function, personality, and symptoms were studied to identify patient predictors of depression severity (measured with the Hamilton Rating Scale for Depression) and complete response (measured with the Hamilton scale and the Beck Depression Inventory). Results: One hundred sixty-two patients completed the entire 16-week trial. Six patient characteristics, in addition to depression severity previously reported, predicted outcome across all treatments:social dysfunction, cognitive dysfunction, expectation of improvement, endogenous depression, double depression, and duration of current episode. Significant patient predictors of differential treatment outcome were identified. 1) Low social dysfunction predicted superior response to interpersonal psychotherapy. 2) Low cognitive dysfunction predicted superior response to cognitive-behavior therapy and to imipramine. 3) High work dysfunction predicted superior response to imipramine. 4) High depression severity and impairment of function predicted superior response to imipramine and to interpersonal psychotherapy. Conclusions: The results demonstrate the relevance of patient characteristics, including social, cognitive, and work function, for prediction of the outcome of major depressive disorder.They provide indirect evidence of treatment specificity by identifying characteristics responsive to different modalities, which may be of value in the selection of patients for alternative treatments.