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.
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.
MLR is robust to non-normality 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.
hazel liao posted on Wednesday, May 27, 2015 - 8:16 am
Floor effects means almost item's response are 1? Ceiling effect means almost item's response are 4?
hazel liao posted on Wednesday, May 27, 2015 - 10:35 am
Thank you ~~~
1. You said MLR is robust to non-normality of continuous variables. However, when I use MLR and the CATEGORICAL option at the same time, in this way categorical data could be analyzed?
2. I want to use cross-lagged panel to analyze data, however a latent variable is from CFA using MLR estimator, the other latent variable is from CFA using WLSMV estimator. In this case, what estimator should I use to conducting cross-lagged?
1. I am not sure what you are asking, but when declaring your variables as Categorical the non-normality robustness is not relevant. And you don't want to replace the Categorical statement with asking for MLR. Asking for Categorical and MLR is fine.
2. Either is fine.
hazel liao posted on Saturday, May 30, 2015 - 12:03 am
Thank you for your response!
I have try the WLSMV estimator to analyze the categorical data, but why there is no residual variance in the model result?
And where could I find the reference to interpretation of the Threshold?
I am running the following cross-lagged model and in the output Mplus is automatically providing covariances between the outcomes variables (Pos_T2, Neg_T2, and Dest_T2). Is there any way to prevent Mplus from automatically specifying these covariances?
Pos_T2 on Pos_T1 Neg_T1 Dest_T1; Neg_T2 on Pos_T1 Neg_T1 Dest_T1; Dest_T2 on Pos_T1 Neg_T1 Dest_T1;