(L)LCA vs GMM PreviousNext
Mplus Discussion > Growth Modeling of Longitudinal Data >
Message/Author
 Trynke Hoekstra posted on Wednesday, February 14, 2007 - 4:52 am
Dear all,

We have data of 126 persons, with 7 timepoints, where on a continuous outcome, the MADRS score (depression) was measured.
To describe the course of the MADRS score over time, we performed an LCA in Mplus (i.e. not mentioning the MIXTURE part in the input). The best fitting result was a 3-cluster model, which seems reasonable and logical.
However, LCA seems to be applicable only for cross sectional data (i.e. not taking into account the longitudinal aspect of our data). GMM might be a better option? However, this is where we get confused. We have followed the example in the users guide, chapter 8 (example 8.1), where time scores are fixed.
Here we get very different results: all but 5 people have been classified into the second cluster. Do you have an idea why this could be? We are first time users of Mplus, so we are not very experienced...
Thanks a lot for your help.
 Trynke Hoekstra posted on Wednesday, February 14, 2007 - 5:08 am
Regarding the above/below:
We made a mistake: for the LCA, we left out the "MODEL" part.
 Linda K. Muthen posted on Wednesday, February 14, 2007 - 9:16 am
You are looking at two different models -- LCA where growth is not taken into account and GMM where it is. Another model that you might want to consider is LCGA. You would not expect to find the same number of classes with different models. You may find the following papers helpful:

Kreuter, F. & Muthen, B. (2006). Analyzing criminal trajectory profiles: Bridging multilevel and group-based approaches using growth mixture modeling.

Muthén, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (ed.), Handbook of quantitative methodology for the social sciences (pp. 345-368). Newbury Park, CA: Sage Publications.

Both of these papers can be downloaded from the website.
 Linda K. Muthen posted on Wednesday, February 14, 2007 - 9:45 am
Another paper, also available on the website, that you may find helpful is:

Kreuter, F. & Muthen, B. (2007). Longitudinal modeling of population heterogeneity: Methodological challenges to the analysis of empirically derived criminal trajectory profiles. Forthcoming in Hancock, G. R., & Samuelsen, K. M. (Eds.). (2007). Advances in latent variable mixture models. Charlotte, NC: Information Age Publishing, Inc.
 Trynke Hoekstra posted on Thursday, February 15, 2007 - 5:23 am
Thanks a lot! All is very new to us, so sometimes we get a little confused. Will look into the papers.
Back to top
Add Your Message Here
Post:
Username: Posting Information:
This is a private posting area. Only registered users and moderators may post messages here.
Password:
Options: Enable HTML code in message
Automatically activate URLs in message
Action: