Cross-lagged models PreviousNext
Mplus Discussion > Growth Modeling of Longitudinal Data >
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 emmanuel bofah posted on Wednesday, January 01, 2014 - 8:04 am
i have a three time point longitudinal data.All students in time point 1 are in time point 2 and and all students in time point 2 are in time point 3. but in time point 2 and 3 more students were included, so there are students in time point 2 and 3 not in time point 1 and students in time 3 not in time point 2 and 1. WHAT IS THE REQUIREMENT FOR CROSS-LAGGED MODELS IN MY CASE.Should i ONLy use the students who were involve in all the three time points for a cross-lagged model or i can use the data as it stands.
 Linda K. Muthen posted on Thursday, January 02, 2014 - 11:47 am
As long as you believe all subjects come from the same population, I would use all available information.
 emmanuel bofah posted on Saturday, January 04, 2014 - 6:45 am
why is it that all cross-lagged models have seen have TWO constructs measured at different time points. Is it a necessary condition or because of complexity.
 Linda K. Muthen posted on Saturday, January 04, 2014 - 1:10 pm
A cross-lagged model requires a minimum of two constricts. You can have more. General questions like this are more appropriate for a general discussion forum like SEMNET.
 hazel liao posted on Thursday, May 21, 2015 - 8:22 am
Hi~
I want to use cross-lagged panel to analysis my data.
There is tow point time longitudinal data.
One of the variable data is normal, so I used ML estimator to conduct CFA to determine the latent variable.
The other data is not normal distributed, so I used MLM estimator to conduct CFA to determine the latent variable.
However, I want to use these tow latent variables which are used different estimator in the CFA to conduct cross-lagged panel. The question is what estimator should I use when I use cross-lagged panel to analysis my data? ML? MLM?

ps. I had used the ML to conduct cross-lagged but the model fit are really poor. Then, I changed the estimator to MLM, the model fit are much better.
 Linda K. Muthen posted on Thursday, May 21, 2015 - 2:54 pm
I would recommend using MLR in both cases. It is also robust to non-normality.
 hazel liao posted on Friday, May 22, 2015 - 4:57 am
Thank you for quickly reply.

Here is one thing I want to make sure, you mean MLR estimator can also be used in the normality data?
 Linda K. Muthen posted on Friday, May 22, 2015 - 7:13 am
Yes.
 hazel liao posted on Friday, May 22, 2015 - 8:20 am
Thank you very much, I will try it.
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