Run a t-test and calculate effect sizes (Cohen's D) using effsize


I am trying to calculate cohen's D effect sizes from group M and SD's using the package effsize

I have a variety of outcome variables and am trying to compare the group means for each outcome between groups (DT/TD) for each level of trial difficulty (simple and complex).

Could anyone please suggest where this may be going wrong or an alternative way to calculate it? <- DT.outcome.summary %>%
filter(group.mean_Double.Support_DT) %>%
group_by(Trial.Difficulty) %>%
t.test(DT, TD, alternative = "two.sided",
paired = TRUE, var.equal = TRUE) %>%
cohen.d(DTorTD == c("DT", "TD"))

t.test() works with vectors not data frames so I think you might want to use it inside a mutate() function.

If you need more specific help, please provide a proper REPRoducible EXample (reprex) illustrating your issue.