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PubMed · 2057658

Variance components and their implications for statistical information in medical data.

E J Orav·T A Louis·R H Palmer·E A Wright
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Abstract

We discuss general issues concerning the design and analysis of medical experiments involving repeated measures or hierarchical groupings of subjects within larger study units. Depending on the types of questions being investigated, the correlations induced by clustering can have dramatic impact on the effective sample size. The unique aspects of such experiments must be accounted for during analysis and during interpretation of the results. We illustrate these issues by using a variance components model to investigate the role of leadership in medical practice.

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Ambulatory CareAnalysis of VarianceBayes TheoremCluster AnalysisData Interpretation, StatisticalHumansLeadershipMonte Carlo MethodPhysician's RoleQuality Assurance, Health CareSampling StudiesJournal ArticleResearch Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.Review

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BibTeXRIS

E J Orav, T A Louis, R H Palmer, E A Wright. 1991. Variance components and their implications for statistical information in medical data.. https://doi.org/10.1002/sim.4780100411

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