Background: Although average-based effect size (ES) and percentage of individual changes (PIC) are quite different, they are not independent: larger ESs lead to higher PICs. However, this association has not been sufficiently explored.
Method: We analyzed this association based on data simulated in the context of a pre-post design, with and without control groups. We simulated various distributions, sample sizes, degrees of test-retest reliability, effect sizes, and different variances in pre- and post-test.
Results: The PIC is closely associated with the ES across a wide variety of empirically frequent scenarios. In the "single group pre-post designs", the linear regression model shows R2 values above 0.90. In the "control group pre-post designs", the linear regression model shows R2 values above 0.80. These results were found even when the post-test variability differed from that of the pre-test, replicating, extending and generalizing the findings in previous studies.
Conclusions: (1) In the absence of information about the PIC, the ES may be used to estimate this percentage. (2) The PIC is useful in interpreting the meaning of ES measures.