Intraclass correlation coefficients typical of cluster-randomized studies: estimates from the Robert Wood Johnson Prescription for Health projects.

Annals of Family Medicine
David M ThompsonJames W Mold

Abstract

Researchers who conduct cluster-randomized studies must account for clustering during study planning; failure to do so can result in insufficient study power. To plan adequately, investigators need accurate estimates of clustering in the form of intraclass correlation coefficients (ICCs). We used data for 5,042 patients, from 61 practices in 8 practice-based research networks, obtained from the Prescription for Health program, sponsored by the Robert Wood Johnson Fund, to estimate ICCs for demographic and behavioral variables and for physician and practice characteristics. We used an approach similar to analysis of variance to calculate ICCs for binary variables and mixed models that directly estimated between- and within-cluster variances to calculate ICCs for continuous variables. ICCs indicating substantial within-practice clustering were calculated for age (ICC = 0.151), race (ICC = 0.265), and such behaviors as smoking (ICC = 0.118) and unhealthy diet (ICC = 0.206). Patients' intent-to-change behaviors related to smoking, diet, or exercise were less clustered (ICCs ≤0.007). Within-network ICCs were generally smaller, reflecting heterogeneity among practices within the same network. ICCs for practice-level measures indicate...Continue Reading

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Oct 18, 2015·BMC Public Health·Kevin FiscellaJonathan Tobin
Nov 27, 2015·Multivariate Behavioral Research·Guillermo VallejoPablo E Livacic-Rojas
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