Fundamental Issues in GGMM PreviousNext
Mplus Discussion > Latent Variable Mixture Modeling >
Message/Author
 Sean Mullen posted on Sunday, May 17, 2009 - 4:56 pm
Regarding "equivalent models" (Muthen, 2003) and testing model assumptions...
1. Is it necessary to check for outliers while using GMM, given that extreme values could be the defining characteristic of classes (for example, do I still need to look at tech13 for Mardia's stat)?
2. The y's making up my classes are normal, covariates are correlated, distal variables are negatively skewed & highly correlated (.4-.6). What should I be concerned with in this scenario?

Defining Class Indicators:
I get different results depending on whether I use a single (avg) class indicator or use the same individual items as separate indicators.
1. Avg score masks individual item contribution, but what might be the advantage to using the average?

Step-wise vs. Simultaneous (Full Model) Approach:
How does one specify MULTIPLE CONTINOUS distal outcomes (and their correlation) while simultaneously using covariates in a GMM? The only syntax I can find uses the savedata option to later test c on u or c on x, but these are never simultaneously specified.

Inspection and Specification of Residual Variances:
IF everything else is equal, can separate models with different class-specific residual constraints be compared or are interpretations of each model different?
 Linda K. Muthen posted on Monday, May 18, 2009 - 3:44 pm
1. You should check for outliers. Use the INFLUENCE setting of the OUTLIERS option.
2. Nothing but possible multicollinearity.

If the latent class indicators are not unidimensional, it does not make sense to add them up. Also, adding them up violates the assumption of conditional independence.

Distal outcomes need appear only on the USEVARIABLES list. See Example 8.6 which has both c ON x and a distal outcome.

You can use MODEL TEST to test equality of residuals.
 Sean Mullen posted on Tuesday, May 19, 2009 - 1:58 pm
Thanks Linda. To clarify, (for outlier plot and to test equality of residuals) in a 3-class model, how would I specify?

MODEL:
[c#1](class1);
!to create a new class variable?;
[c#2](class2);
MODEL TEST: 0=class1-class2;

PLOT:
OUTLIERS=INFLUENCE

***I am clearly doing something very wrong because I not only get errors, but when I just try to the plot, my mplus needs to shutdown because of a windows error. It happens every time.
 Linda K. Muthen posted on Wednesday, May 20, 2009 - 1:21 am
Please send your input, data, output, and license number to support@statmodel.com.
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: