Approaches to effect size selection for power analysis

Abstract

Researchers routinely have to decide upon the sample size they include in their research. When formal sample size planning is used it is important to understand that the approach to sample size selection (e.g., AIPE or power analysis) as well as the method used to develop the alternative hypothesis (i.e., the effect sizes and parameter estimates used in power analysis) has important implications for the appropriate interpretation of the results. This paper presents the results of analysis of the sample size planning approach used in 121 empirical research articles published in the November 2017 to August 2018 issues of Psychological Science, and uses the results of this analysis to illustrate a guide to sample size planning under the most common methods of sample size determination (power analysis, Accuracy in Parameter Estimation, Statistical Assurance, and Bayesian sample size determination)