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 Megan Whelen posted on Thursday, June 13, 2019 - 1:33 pm

Iím running a cross-classified DSEM model with continuous variables. I based my code on example 9.39 in the Mplus User Guide. In the example, the random intercept of y, random linear trend of y, and random slope of y on x are all regressed on the subject-level covariates. In my model, I only regress the random slope on my covariate, as that is the only effect I am interested in estimating. Are there any unanticipated consequences of leaving out the regression of the random intercept and random linear trend on the covariate?

Second, the unstandardized estimate I get when I regress the random slope on my covariate is .005. What is the interpretation of this number? Iíve noticed the options STD, STDY, and STDYX are not available when TYPE = CROSSCLASSIFIED RANDOM. Is there another way to get standardized estimates?
 Bengt O. Muthen posted on Thursday, June 13, 2019 - 5:07 pm
If you leave them out, you are saying that they are unrelated (uncorrelated) with the covariate. I would include them even if that's not of primary interest.

You can use a regular standardization approach because you know the variance of both the DV and the IV.
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