I want to calculate cohen's d with confidence intervals for a paired samples designs.
Some authors suggest that you use the paired t test value to adjust for the correlation between measures (Rosenthal, 1991).
However, Dunlop et al 1996 suggest that the correlation between the paired samples should not be included. In particular, if such a correlation is used, then results are not readily comparable to between subjects effects. Instead, they recommend using independent samples formula:
How do you estimate confidence intervals for Cohen's d in a paired samples design where Cohen's d uses the formula above?
The way I have estimated it so far is to use the R function
ci.smd from the MBESS package. This function is designed for independent samples tests and takes the sizes of two independent groups as input.
In the code below I use
i to represent the number of subjects (equal, as the same participants are in each group) and use an effect size of 0.8 as an example.
library(MBESS) x.ci <- ci.smd(smd=0.8, n.1=i,n.2=i)
Is it appropriate to use such function
ci.smd for confidence intervals for paired samples?