Anonymous posted on Monday, August 26, 2002 - 3:18 pm
In the MPLUS specification of a LCGA, does one need to explicitly specify that the variances of growth parameters and the covariances between growth parameter within class are equal to zero? I searched through your examples, but could not find a set-up for the LCGA. Thank you!
The LCGA and GMM models are the same for continuous and categorical outcomes. LCGA fixes variances and covariances for the growth factors at zero while GMM has free growth factor variances and covariances. For categorical outcomes, numerical integration is required for model estimation for GMM but not for LCGA.
This confirm what I tought. But I think my question was not clear.
In the Mplus input for non-continuous outcomes LCGA, if we dont specify "numerical integration" then do we still have to specify i@0; s@0; i WITH s @0. In the manual examples, no such specification are given for the non-continuous outcomes LCGA (ex 8.9, 8.10, 8.11).
Can a latent class growth analysis be performed when the indicators are dichotomous? Is it OK to construct a latent growth model with the latent intercept and slope factors as we typically think of them, when the indicators proceed in 0-1 patterns such as 0-0-0-1 or 0-1-1-1 or 0-0-1-1?
Or would this be inappropriate for a latent growth model? If so, is there another model that you can suggest? I am very interested in the mixture models in Chapter 8 of the Mplus manual, but I am not sure if they are appropriate for my analysis.
Thank you, could aspects of the models in Chapter 8 be combined?
I like the model shown in EXAMPLE 8.7: A SEQUENTIAL PROCESS GMM, as we have two sequential processes--but could I adapt it: a) to have known classes as in Example 8.8, and b) to have dichotomous outcomes rather than continuous?