Simplified Tools for Sample Size Determination for Correlation Coefficient Inference

• Activity Number: 651
• Type: Contributed
• Date/Time: Thursday, August 4, 2016 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistical Computing
• Author(s): Stephen W. Looney and Justine May* and Jessica McKinney Ketchum
• Companies: Augusta University and Augusta University and Craig Hospital
• Keywords: Effect size ; Confidence interval ; Pearson correlation ; Spearman correlation ; Kendall coefficient ; Power

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. In this presentation, we discuss the issues associated with sample size determination for bivariate correlation analysis and provide simplified tools, including nomograms, for determining the required sample size. These tools make use of recent improvements in methods for sample size calculations for correlation analysis. Tools are provided that can be used for sample size determination for Pearson, Spearman, and Kendall coefficients.