Intention-to-treat analysis in cluster randomized trials with noncompliance.
In cluster randomized trials (CRTs), individuals belonging to the same cluster are very likely to resemble one another, not only in terms of outcomes but also in terms of treatment compliance behavior. Although the impact of resemblance in outcomes is well acknowledged, little attention has been given to the possible impact of resemblance in compliance behavior. This study defines compliance intraclass correlation as the level of resemblance in compliance behavior among individuals within clusters. On the basis of Monte Carlo simulations, it is demonstrated how compliance intraclass correlation affects power to detect intention-to-treat (ITT) effect in the CRT setting. As a way of improving power to detect ITT effect in CRTs accompanied by noncompliance, this study employs an estimation method, where ITT effect estimates are obtained based on compliance-type-specific treatment effect estimates. A multilevel mixture analysis using an ML-EM estimation method is used for this estimation.
Jo
Booil
B
Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305-5795, U.S.A. booil@stanford.edu
Asparouhov
Tihomir
T
Muthén
Bengt O
BO
D000465:Algorithms; D002648:Child; D002653:Child Behavior Disorders / Q000517:prevention & control / Q000628:therapy*; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D005500:Follow-Up Studies; D006801:Humans; D033182:Intention; D016015:Logistic Models; D009010:Monte Carlo Method; D010290:Parents; D010349:Patient Compliance / Q000706:statistics & numerical data*; D016032:Randomized Controlled Trials as Topic; D013997:Time Factors; D016896:Treatment Outcome