Student 09 posted on Monday, January 16, 2012 - 4:33 am
using the multiple group analysis in Mplus, I would like to test whether an indirect effect differs between two subsamples (group a & group b).
For each group, I requested the indirect effect by using the model constraint command.
y2 ON y1 (p1a); y1 ON x (p2a);
MODEL CONSTRAINT: NEW (ind_1); Ind_1 = p1a*p2a;
MODEL group b:
y2 ON y1 (p1b); y1 ON x (p2b);
MODEL CONSTRAINT: NEW (ind_2); Ind_2 = p1b*p2b;
This syntax yields the two indirect effects (ind_1 & ind_2). But now I wonder how to test their difference – how would I constrain these parameters to be equal, given that they come from two different groups?
You can run moderated mediation using multiple group analysis but you can't use MODEL INDIRECT. You will need to use MODEL CONSTRAINT to compare indirect effects across groups. MODEL INDIRECT does not have this function.
How do I test whether multiple indirect effects differ between 2 groups? The model includes paths from 2 Xs (ext2, stigma2) through a single mediator (ai_t) to 2 DV's (VDATE, PDATE).
I used the model constraint language as per Bengt's response above to create the 4indirect diffs... MODEL CHILD: ai_t on ext_pt2 (a1a); ai_t on STIGMA2 (a2a); PDATE on ai_t (b1a); VDATE on ai_t (b2a); MODEL ADOLESCENT: ai_t on ext_pt2 (a1b); ai_t on STIGMA2 (a2b); PDATE on ai_t (b1b); VDATE on ai_t (b2b); MODEL CONSTRAINT: NEW (ind_1 ind_2 diff); ind_1 = a1a*b1a; ind_2 = a1b*b1b; diff = ind_1-ind_2; NEW (ind_3 ind_4 diff); ind_3 = a2a*b1a; ind_4= a2b*b1b; diff = ind_3-ind_4; NEW (ind_5 ind_6 diff); ind_5 = a1a*b2a; ind_6 = a1b*b2b; diff = ind_5-ind_6; NEW (ind_7 ind_8 diff); ind_7 = a2a*b2a; ind_8 = a2b*b2b; diff = ind_7-ind_8;
Mplus will run a single constraint test but when I include more than one I get an error message saying that I've entered an already used parameter. Although true, each indirect is comprised of unique pairs of parameters. Is there a way to simultaneous test differences in the 4 indirect effects?
In using the MODEL CONSTRAINT option to define new parameters for one's model, does this increase the number of parameters estimated and hence affect degrees of freedom?
A five-knownclass model in which I used MODEL CONSTRAINT to define an a*b indirect path (to test for mediation) had different degrees of freedom than I expected, and I wondered if this is because I added parameters to the model through using this command?
Thanks, Linda. Can I label parameters that are class-specific estimates in a knownclass model, then use those class-specific labels to constrain parameters within classes? For example--would this work?