Jo Brown posted on Wednesday, May 16, 2012 - 4:47 am
I am exploring a simple mediation model and would like to adjust it for confounders (z1 - z5) which I believe may influence the c path (X--> Y).
I am not sure where/how to specify them. Should they be included in all regressions statements or just the Y on X one (as below)?
Should they also be specified in the MODEL INDIRECT command as well?
Model: Y on m ; Y on X z1 z2 z3 z4 z5; m on X;
MODEL INDIRECT: Y IND X;
Emil Coman posted on Wednesday, May 16, 2012 - 11:11 am
I would try to take a stab at this, if I may: Judd & Kenny (2009) list this as the most problematic assumption, that m and Y have no common causes (p. 117), so you are doing what few researcher do (great!). In your case, it seems you want to add : m on z1 z2 z3 z4 z5; And the INDIRECT command should be fine, just make it Y IND m X; INDIRECT is going to estimate the effect flowing from X through m, which will not go through the confounders too. Judd, C., & Kenny, D. (2009). Data Analysis in Social Psychology: Recent and Recurring Issues. In S. T. Fiske, D. T. Gilbert & G. Lindzey (Eds.), Handbook of Social Psychology, Volume One (pp. 113-137). Hoboken, NJ: Wiley. Cheers, emil
I have a mediation model with measures collected at 3 time points: x1->m2->y3.
I recently read the paper by Cole & Maxwell (2003) who suggest that to adjust a mediation model it is necessary to adjust path a for the mediator at baseline (i.e. time 1) to capture the actual change. I am not sure whether it is sufficient to do so or whether I should also adjust the other paths with m1 so that