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Methods To Reduce The Impact Of Intraclass Correlation In Group-Randomized Trials

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  • David M. Murray
  • Jonathan L. Blitstein

Abstract

This study reports intraclass correlation (ICC) for dependent variables used in group-randomized trials (GRTs). The authors also document the effect of two methods suggested to reduce the impact of ICC in GRTs; these two methods are modeling time and regression adjustment for covariates. They coded and analyzed 1,188 ICC estimates from 17 published, in press, and unpublished articles representing 21 studies. Findings confirm that both methods can improve the efficiency of analyses shown to be valid across conditions common in GRTs. Investigators planning GRTs should obtain ICC estimates matched to their planned analysis so that they can size their studies properly.

Suggested Citation

  • David M. Murray & Jonathan L. Blitstein, 2003. "Methods To Reduce The Impact Of Intraclass Correlation In Group-Randomized Trials," Evaluation Review, , vol. 27(1), pages 79-103, February.
    • Handle: RePEc:sae:evarev:v:27:y:2003:i:1:p:79-103
    DOI: 10.1177/0193841X02239019
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    References listed on IDEAS

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    1. P. Diggle & M. G. Kenward, 1994. "Informative Drop‐Out in Longitudinal Data Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(1), pages 49-73, March.
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    Cited by:

    1. Satoshi Usami, 2017. "Generalized SAMPLE SIZE Determination Formulas for Investigating Contextual Effects by a Three-Level Random Intercept Model," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 133-157, March.
    2. Steven Teerenstra & Bing Lu & John S. Preisser & Theo van Achterberg & George F. Borm, 2010. "Sample Size Considerations for GEE Analyses of Three-Level Cluster Randomized Trials," Biometrics, The International Biometric Society, vol. 66(4), pages 1230-1237, December.

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