Computing Cohen’s dz from commonly reported statistics: a practical guide for the meta-analysis of paired samples mean differences

The typical approach to computing standardised mean differences (d) from paired-samples (or within-subjects) designs requires knowing the often-unreported repeated-measures correlation, r_"repeated" . This adjustment enables comparison with ds from independent samples. However, when meta-analysing effects that come exclusively from paired samples, an underutilised option is to compute Cohen’s d_z, which does not require r_"repeated" . Because d_z can be computed from a range of summary and inferential statistics, it enables researchers to obtain standardised effects even when articles report their results in little detail. The present article contains equations and the corresponding R code needed to compute d_z and its variance, and adjust for small-sample bias.