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 Lucia Salinas posted on Wednesday, April 22, 2015 - 5:04 am
Hello Drs Muthen,

I specified a cross-lagged model using MLR with two waves and 5 variables (1 = manifest, continuous + 4 = latent factors assuming strong measurement invariance). This model and moderations by age and gender (via multi-group) worked fine.

I was asked to rerun this model including only manifest, binary variables to assess the clinical meaningfulness. I'm wondering if it's adequate to specify such a model? If yes, is this specification done properly using WLSMV:

X2-4 ON age gender SES;

Y2-4 ON age gender SES;

X1 WITH X2 X3 X4 X5;
X2 WITH X3 X4 X5;
X3 WITH X4 X5;

Y1 WITH Y2@0 X3@0 X4@0 X5@0;
Y2 WITH Y3@0 X4@0 X5@0;
Y3 WITH Y4@0 X5@0;
Y4 WITH Y5@0;

Y2 ON X2 X1;
Y1 ON X1 X2;
Y3 ON X3 X1;
Y1 ON X1 X3;
Y4 ON X4 X1;
Y1 ON X1 X4;
Y5 ON X5 X1;
Y1 ON X1 X5;

In addition, would you recommend allowing correlations between manifest variables at t2.

Thanks for your help in advance and kind regards!
 Bengt O. Muthen posted on Wednesday, April 22, 2015 - 2:05 pm
Looks ok although I don't understand the argument for dichotomizing to study clinical significance. Regarding correlating variables as t2, I would discuss on SEMNET.
 Lucia Salinas posted on Thursday, April 23, 2015 - 6:29 am
Thank you for your quick response. The variables assessed can be categorized into "normal" vs. "abnormal" scores on the basis of recommended cutoff scores for clinical diagnoses.
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