Subject-level matching for imbalance in cluster randomized trials with a small number of clusters

• Published in: Pharmaceutical statistics : the journal of the pharmaceutical industry Vol. 12; no. 5; pp. 268 - 274
• Main Authors: Leon, Andrew C., Demirtas, Hakan, Li, Chunshan, Hedeker, Donald
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.09.2013; Wiley Subscription Services, Inc
• Subjects: Aged; bias reduction; Cluster Analysis; cluster randomized controlled trials; Humans; propensity adjustment; Propensity Score; Randomized Controlled Trials as Topic - statistics & numerical data; Suicide - prevention & control; Suicide - statistics & numerical data; propensity adjustment; cluster randomized controlled trials; bias reduction
• ISSN: 1539-1604; 1539-1612; 1539-1612
• DOI: 10.1002/pst.1580

In a cluster randomized controlled trial (RCT), the number of randomized units is typically considerably smaller than in trials where the unit of randomization is the patient. If the number of randomized clusters is small, there is a reasonable chance of baseline imbalance between the experimental and control groups. This imbalance threatens the validity of inferences regarding post‐treatment intervention effects unless an appropriate statistical adjustment is used. Here, we consider application of the propensity score adjustment for cluster RCTs. For the purpose of illustration, we apply the propensity adjustment to a cluster RCT that evaluated an intervention to reduce suicidal ideation and depression. This approach to adjusting imbalance had considerable bearing on the interpretation of results. A simulation study demonstrates that the propensity adjustment reduced well over 90% of the bias seen in unadjusted models for the specifications examined. Copyright © 2013 John Wiley & Sons, Ltd.