Mixture Regression PreviousNext
Mplus Discussion > Latent Variable Mixture Modeling >
Message/Author
 Chris Weber posted on Wednesday, July 29, 2009 - 7:12 pm
Hello,

I have two outcome variables, which are both bimodal and continuous. I am trying to fit a two class mixture model:

NAMES ARE
DOLKEPT EFFORT
TOM d1 d2 d3 d4 d5 d6
d1xeyes d2xeyes d3xeyes
d4xeyes d5xeyes
d6xeyes;

USEVARIABLES ARE
DOLKEPT EFFORT;

CLASSES=c(2);

ANALYSIS:
TYPE=MIXTURE;
STARTS=100 20;

model:
%overall%

I get this error:

THE STANDARD ERRORS OF THE MODEL PARAMETER ESTIMATES MAY NOT BE TRUSTWORTHY FOR SOME PARAMETERS DUE TO A NON-POSITIVE DEFINITE
FIRST-ORDER DERIVATIVE PRODUCT MATRIX. THIS MAY BE DUE TO THE STARTING
VALUES BUT MAY ALSO BE AN INDICATION OF MODEL NONIDENTIFICATION. THE
CONDITION NUMBER IS -0.101D-16. PROBLEM INVOLVING PARAMETER 2.

I've tried specifying my own starting values,as well as increasing the number of random starts, but haven't had any luck. Am I missing something? Are there parameter restrictions that should be made?

Thanks,
Chris
 Linda K. Muthen posted on Wednesday, July 29, 2009 - 10:41 pm
This should work. Please send your full 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: