Description
I've run into an issue where I'm getting slightly different results, especially with smaller (e.g., N ≤ 30) sample sizes, when I run moderation analyses with medmod (versus results from the equivalent model specified using a general linear model). Specifically, the Z values (and associated p values) for the parameter estimates from medmod are off a bit when comparing them with the equivalent t (and p) values for parameter estimates.
My understanding is that this arises because the med/mod functions in the medmod module are scaffolded onto lavaan, which runs a Wald test and computes Z-statistics that are tested against a chi-square (vs student's t) distribution. Many times, Wald (and vanilla t) tests will lead you to the same decision/inference (i.e., to reject the null or not). But, it seems that with smaller sample sizes the p-values can be different and that can be problematic.
If possible, could a future release of medmod give the option of computing t (and associated p) values instead of the Wald test (with z and p values) inherited from lavaan?