Hello: I have a multigroup SEM model that has x->y which is partially mediated by two variables M1 and M2 such that x->y and x->M1->y and x->M2->y.
The grouping variable is dichotomous 0 = low and 1 = high. I am using type=complex as it is a complex sample design.
I would like to estimate the bias corrected bootstrapped SE, but you can't do that with type = complex. Is there a work around for this? For example if I were to create a phantom variable and fix its path (to x) to be the product of the x->m->y paths, then remove type = complex, would I get reliable bias-corrected SE for the phantom variable path since its fixed or would removing the type=complex create unreliable coefficients.