articleTop 10% cited
Sample size and optimal designs for reliability studies
Statistics in Medicine · 1998 · Vol. 17(1) · pp. 101–110
Stephen D. Walter✉(McMaster University)Michael Eliasziw(Robarts Clinical Trials)Allan Donner(Western University)
Abstract
A method is developed to calculate the required number of subjects k in a reliability study, where reliability is measured using the intraclass correlation rho. The method is based on a functional approximation to earlier exact results. The approximation is shown to have excellent agreement with the exact results and one can use it easily without intensive numerical computation. Optimal design configurations are also discussed; for reliability values of about 40 per cent or higher, use of two or three observations per subject will minimize the total number of observations required.
Optimal Experimental Design MethodsStatistical Methods and Bayesian InferenceReliability (semiconductor)Intraclass correlationComputationSample size determinationComputer scienceApplied mathematicsStatisticsMathematicsOptimal designReliability engineering
MeSH terms
Analysis of VarianceChildDown SyndromeHumansOntarioPsychometricsResearch DesignReproducibility of ResultsObserver VariationSample Size
Funding
- Health Canada
Citations
2,129
FWCI
8.88
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