Computing the Confidence Interval for the Effect Size Cohen’s d

Abstract

The effect size Cohen’s d allows for a quantitative and metric-free estimation of an effect. This effect can be the result of the deviation of a mean value from a certain value or the mean difference between two samples. The precision of this estimation is given by the width of a confidence interval for the effect size Cohen’s d. The aim of this article is to show the importance of noncentral t distributions for a precise estimation of confidence intervals for Cohen’s d and to explain how to compute them. On the Open Science Framework online platform, two programs in R are freely available that calculate the confidence intervals for Cohen’s d for one or two samples based on the following input variables: confidence level (e.g. 95%), sample size(s), mean(s) and standard deviation(s). The article concludes by illustrating the discussed approach with an example.