I am running a series of multiple mediation models. Each model includes one IV, two mediators, and a DV. I’m using a macro created for SPSS (provided by Preacher and Hayes) that uses bootstrapping to examine the indirect effects of the mediators. My DV’s are depression and social anxiety (each run in a separate model) and are both positively skewed. Normally I would perform a log transformation on these variables, however, bootstrapping is a nonparametric resampling procedure that does not hold the assumption of normality of the sampling distribution. Therefore, my question is: Is it necessary to transform positively skewed DV’s even though I am using bootstrapping?
Note: I have run my models with the log transformed means vs. untransformed means for the DV’s and the pattern of results are essentially the same. However, I would prefer to use the untransformed means as the unstandardized regression coefficients more strongly support my predictions.