An elaboration on sample size determination for correlations based on effect sizes and confidence interval width: a guide for researchers

Abstract

Objectives This paper aims to serve as a useful guide for sample size determination for various correlation analyses that are based on effect sizes and confidence interval width. Materials and Methods Sample size determinations are calculated for Pearson’s correlation, Spearman’s rank correlation, and Kendall’s Tau-b correlation. Examples of sample size statements and their justification are also included. Results Using the same effect sizes, there are differences between the sample size determination of the 3 statistical tests. Based on an empirical calculation, a minimum sample size of 149 is usually adequate for performing both parametric and non-parametric correlation analysis to determine at least a moderate to an excellent degree of correlation with acceptable confidence interval width. Conclusions Determining data assumption(s) is one of the challenges to offering a valid technique to estimate the required sample size for correlation analyses. Sample size tables are provided and these will help researchers to estimate a minimum sample size requirement based on correlation analyses.