The exact confidence interval of the Cohen's d in repeated measure design
Cohen's d, also called the standardized mean difference, is one of the most used effect sizes. Reporting confidence intervals for effect sizes is customary (and strongly recommended by many journals). However, there was no known exact confidence interval when the means were obtained in a repeated-measures design (also called a within-subject design or a paired sample). Herein, I provide the exact confidence interval of Cohen's d in repeated-measures designs. It is influenced by the correlation between the pairs of measures and so the confidence interval is exact in situations where the population correlation is known. I also propose a Bayesian credible interval when only the sample correlation is known. A package for R is briefly presented which performs the computations.
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