|
|
Longitudinal patterns of multivariate... |
|
Message/Author |
|
Liang posted on Friday, April 08, 2011 - 8:38 am
|
|
|
Dear Dr. Muthen & Muthen, I have a question about how to use Mplus to define longitudinal patterns of multivariate psychological variables. We have three observation time points (j=1,2,3). In j-th observation time we observe distress score (Y_j1), somatization score (Y_j2), and anxiety score (Y_j3). If at each observation time we use a global score (Y_j) for the three variables, it is easy to write the code as following, suppose we want 4 classes. Usevariables are Y_1 Y_2 Y_3; Classes=c(4); But the investigator insists to use three variables at each time point to classify 4 longitudinal patterns (not three independent models for distress, somatization, anxiety, separately). Then can I write as the following? Usevariables are Y_11 Y_12 Y_13 Y_21 Y_22 Y_23 Y_31 Y_32 Y_33; Classes=c(4); If it is wrong to write in this way, what should I do? Do you have any similar example for me to refer? Thank you very much for your answer! |
|
|
You can write it the way you propose. Your model becomes a parallel process model (although with 3 instead of 2 processes). See the UG index for such a model. To which it sounds like you want to add one latent class variable that is determined by all 3 processes. |
|
MCA posted on Thursday, January 16, 2014 - 7:57 pm
|
|
|
Hello, I am wondering if it's possible to estimate a series of such models with increasing numbers of categorical latent variables, and then test how many categorical latent variables are needed. If so, do you have examples/guidance on how to perform such model comparisons? Finally, is it possible to combine categorical and continuous manifest variables in this setting (like you can do for cross-sectional LCA)? If so, is there an example anywhere of this? Thanks in advance! |
|
|
Are you referring to the above discussion from April 2008? |
|
MCA posted on Friday, January 17, 2014 - 9:13 am
|
|
|
Hi, Sorry for not being clearer - I was referring to the discussion from April 08, 2011. The original question was: "I have a question about how to use Mplus to define longitudinal patterns of multivariate psychological variables. We have three observation time points (j=1,2,3). In j-th observation time we observe distress score (Y_j1), somatization score (Y_j2), and anxiety score (Y_j3). If at each observation time we use a global score (Y_j) for the three variables, it is easy to write the code as following, suppose we want 4 classes. Usevariables are Y_1 Y_2 Y_3; Classes=c(4); But the investigator insists to use three variables at each time point to classify 4 longitudinal patterns (not three independent models for distress, somatization, anxiety, separately). Then can I write as the following? Usevariables are Y_11 Y_12 Y_13 Y_21 Y_22 Y_23 Y_31 Y_32 Y_33; Classes=c(4); If it is wrong to write in this way, what should I do? Do you have any similar example for me to refer? Thank you very much for your answer!" Thanks so much! |
|
|
When I read this message now, I interpret it as a multiple (distress, somati, anx) indicator model for a single factor at 3 time points rather than a parallel process model. But BIC can be used in both cases to decide on the number of latent classes that are needed. You can combine any types of observed variables. |
|
Back to top |
|
|