I estimated a growth curve model with 5 waves 2 latent predictors (observed indicators for these latent constructs are continuous, categorical and nominal) and 5 observed controls. I would like to plot trajectories for latent construct values. Is there anyway I can get/calculate wave specific estimates for Low vs High values of the latent constructs for example?
There is not an automatic way to plot this in Mplus. But you can compute from the estimated model the estimated means and variances for the latent constructs at each time point. Then you can choose a low/high value for the construct at each time point as say -1SD/+1SD off the mean. For those values you can then compute the observed variable mean at each time point and plot that. You can do this for example in Excel.
Thanks Bengt that was helpful. I have another question regarding assessment of model fit. As mentioned in my previous note, my model contains 2 latent predictors where the observed indicators are a mix of continuous, categorical and nominal observed measures. Using MLR, MPLUS does not produce the standard fit measures that I usually use to assess model fit. Any suggestions on what to use in this case to show/evidence model fit.
You can do difference testing using the loglikelihood. With MLR, you need to use the scaling correction factor provided in the output. This is described on the website under Chi-Square Difference Test for MLM and MLR.