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Sherri L. Pals, PhD, David M. Murray, PhD, Catherine M. Alfano, PhD, William R. Shadish, PhD, Peter J. Hannan, MStat and William L. Baker, BS

Sherri L. Pals is with the Division of HIV/AIDS Prevention, National Center for HIV, Viral Hepatitis, STD and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA. David M. Murray is with the Division of Epidemiology, College of Public Health, Ohio State University, Columbus. Catherine M. Alfano is with the Division of Health Behavior and Health Promotion, College of Public Health, and the Comprehensive Cancer Center, Ohio State University. William R. Shadish is with the School of Social Sciences, Humanities and Arts, University of California, Merced. Peter J. Hannan and William L. Baker are with the Division of Epidemiology and Community Health, University of Minnesota, Minneapolis.

Correspondence: Requests for reprints should be sent to Sherri L. Pals, PhD, MS E-45, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA 30333 (e-mail: sfv3{at}cdc.gov).

ABSTRACT

Objectives. We reviewed published individually randomized group treatment (IRGT) trials to assess researchers’ awareness of within-group correlation and determine whether appropriate design and analytic methods were used to test for treatment effectiveness.

Methods. We assessed sample size and analytic methods in IRGT trials published in 6 public health and behavioral health journals between 2002 and 2006.

Results. Our review included 34 articles; in 32 (94.1%) of these articles, inappropriate analytic methods were used. In only 1 article did the researchers claim that expected intraclass correlations (ICCs) were taken into account in sample size estimation; in most articles, sample size was not mentioned or ICCs were ignored in the reported calculations.

Conclusions. Trials in which individuals are randomly assigned to study conditions and treatments administered in groups may induce within-group correlation, violating the assumption of independence underlying commonly used statistical methods. Methods that take expected ICCs into account should be used in reexamining past studies and planning future studies to ensure that interventions are not judged effective solely on the basis of statistical artifacts. We strongly encourage investigators to report ICCs from IRGT trials and describe study characteristics clearly to aid these efforts.