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| Options for twolevel mediation analysis |
 
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Drs. Muthen,
I am estimating the LGC mediation model as described in MacKinnon's book (p.209), in which the x, m, and y variables represent intercept and slope factors:
ANALYSIS: TYPE = TWOLEVEL RANDOM;
MODEL:
%WITHIN%
! latent growth for x, m, & y;
XI BY X1@1 X2@1 X3@1 X4@1;
XS BY X1@0 X2@1 X3@2 X4@3;
...
! Mediation ;
as | MS ON XS ;
bs | YS ON MS ;
%BETWEEN%
AS WITH BS (CABS);
If I understand correctly, neither the INDIRECT option nor bootstrapped CIs are available for this model. Therefore, I specify the indirect effects as
MODEL CONSTRAINT:
NEW(INDS);
INDS=AS*BS+CABS;
...and request CIs with the CINTERVAL option.
Is my understanding correct, and do you have any recommendations for testing the mediation effects? Would a Monte Carlo approach similar to Selig and Preacher's MCMAM approach be possible?
Thanks. |
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| Assuming you have 2-level data (and not only level1=time, level2=person), that is, clusters, this looks correct, except that in Model Constraint you should have MAS and MBS, where those are labels on the Between for the means of the random slpoes as and bs, respectively. Model constraint gives you standard errors for this indirect effect via the Delta method. |
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