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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 CROSSLAGGED MODELS IN MY CASE.Should i ONLy use the students who were involve in all the three time points for a crosslagged model or i can use the data as it stands. 


As long as you believe all subjects come from the same population, I would use all available information. 


why is it that all crosslagged models have seen have TWO constructs measured at different time points. Is it a necessary condition or because of complexity. 


A crosslagged 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 crosslagged 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 crosslagged panel. The question is what estimator should I use when I use crosslagged panel to analysis my data? ML? MLM? ps. I had used the ML to conduct crosslagged but the model fit are really poor. Then, I changed the estimator to MLM, the model fit are much better. 


I would recommend using MLR in both cases. It is also robust to nonnormality. 

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? 


Yes. 

hazel liao posted on Friday, May 22, 2015  8:20 am



Thank you very much, I will try it. 

hazel liao posted on Wednesday, May 27, 2015  2:09 am



Hi~ I have one more question. Could the categorical data which has 4 categories be regarded as nonnormality data? And, could I still use the MLR estimator to the categorical data? Thank you~ 


MLR is robust to nonnormality of continuous variables. Categorical data methodology takes care of any floor or ceiling effects of categorical variables. Using WLSMV or MLR and the CATEGORICAL option takes care of this. 

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