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Sample Size Charts for Spearman and Kendall Coefficients

Justine O. May, Stephen W. Looney

2020Journal of Biometrics & Biostatistics40 citationsDOI

Abstract

Bivariate correlation analysis is one of the most commonly used statistical methods. Unfortunately, it is generally the case that little or no attention is given to sample size determination when planning a study in which correlation analysis will be used. For example, our review of clinical research journals indicated that none of the 111 articles published in 2014 that presented correlation results provided a justification for the sample size used in the correlation analysis. There are a number of easily accessible tools that can be used to determine the required sample size for inference based on a Pearson correlation coefficient; however, we were unable to locate any widely available tools that can be used for sample size calculations for a Spearman correlation coefficient or a Kendall coefficient of concordance. In this article, we provide formulas and charts that can be used to determine the required sample size for inference based on either of these coefficients. Additional sample size charts are provided in the Supplementary Materials.

Topics & Concepts

Sample size determinationBivariate analysisSpearman's rank correlation coefficientStatisticsPearson product-moment correlation coefficientSample (material)Correlation coefficientComputer scienceCorrelationInferenceStatistical inferenceData miningMathematicsArtificial intelligenceChromatographyGeometryChemistryStatistical Methods in Clinical Trials