Parameters to aid in the design and analysis of community trials: Intraclass correlations from the minnesota heart health program

Peter J Hannan, David M. Murray, David R Jacobs Jr, Paul G. McGovern

Research output: Contribution to journalArticlepeer-review

82 Scopus citations

Abstract

Community trials involve the assignment of intact social groups to study conditions and are becoming increasingly common in epidemiologic research. In both the design and analysis of these studies, whether cross-sectional or cohort, allowance must be made for the dependence of elements within intact groups if variances are to be properly estimated. In the design phase, the statistician needs estimates of the level of dependence likely to be encountered. In the analysis phase, external estimates of the level of dependence may be useful in preventing the erosion of power associated with small numbers of intact groups assigned to each condition. We report the intraclass correlation coefficients of the city- year component of variance as estimated in the Minnesota Heart Health Program for a variety of community survey variables and illustrate their use in both design and analysis. of 23 variables assessed, all but two showed positive estimates of city-year intraclass correlations. In these data, estimates of intradass correlation coefficients generally were in the range 0.002–0.012.

Original languageEnglish (US)
Pages (from-to)88-95
Number of pages8
JournalEpidemiology
Volume5
Issue number1
DOIs
StatePublished - Jan 1994

Keywords

  • Cluster designs
  • Community surveys
  • Component of variance
  • Data analysis
  • Intradass correlation
  • Nested designs
  • Study design

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