A paired t-test is a within-subjects design, so you are right on that point. But it has only one fixed effects factor with two levels and so only one comparison. Your scenario is more complicated, and the stat model cannot be a paired t-test.   ... View more

Hi and sorry for the delay. No, I got this "ERROR: Result of WHEN clause 17 is not the same data type as the preceding results." Only this ending (suggested here before) worked: else '' end as Cond from step2.Clean; quit ##- Please type your reply above this line. Simple formatting, no attachments. -## ... View more

Effect size as defined elsewhere for Cohen's d  for continuous variables is generally the ratio of the observed difference in means to the pooled standard deviation.  Once you hit mixed models, the concept of pooled standard deviation becomes murky.  And, unfortunately, it can carry over to the difference in means, as can be seen by looking at various covariance structures and random effects models, especially if there is imbalance.  This is because the estimates are obtained by maximizing the likelihood (or integrating the likelihood numerically) over both fixed and random effects.  As a result, several of the assumptions for the standard measures of effect size are not met.  Differences are conditional on the random (or repeated) effects.   This article shows how to extract Cohen's f^2 from PROC MIXED, which may be more appropriate here.   https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3328081/   Steve Denham ... View more