Troubleshooting errors with time-vary... PreviousNext
Mplus Discussion > Growth Modeling of Longitudinal Data >
Message/Author
 Amber Fahey posted on Wednesday, November 15, 2017 - 6:05 pm
Hello, I am trying to identify the rate and trajectory of orientation in patients with moderate and severe TBI while in acute rehabilitation. Administration of test was on different days, and different number of times so I am using wide format, and commands outlined in example 6.12 of the manual. I have 20 administrations but I have to adjust coverage to 0.001. I also get a warning:
WARNING: THE MODEL ESTIMATION HAS REACHED A SADDLE POINT OR A POINT WHERE THE
OBSERVED AND THE EXPECTED INFORMATION MATRICES DO NOT MATCH.
AN ADJUSTMENT TO THE ESTIMATION OF THE INFORMATION MATRIX HAS BEEN MADE.
THE CONDITION NUMBER IS -0.183D-03.
THE PROBLEM MAY ALSO BE RESOLVED BY DECREASING THE VALUE OF THE
MCONVERGENCE OR LOGCRITERION OPTIONS OR BY CHANGING THE STARTING VALUES
OR BY USING THE MLF ESTIMATOR.

1. Is there a recommended minimum value for coverage?
2. I have read that it is recommended to adjust sample variances to 1-10 using the DEFINE command but I am not sure which variances to look at to determine this.
3. How do I determine what to adjust the MCONVERGENCE value to, and the number of iterations, and starting values?
4. How do you adjust Logcriterion/what does the warning mean when it says to use LOGCRITERION OPTIONS?
5. What order of corrections do you suggest I do/start with?
 Linda K. Muthen posted on Thursday, November 16, 2017 - 6:12 am
Please send the output and your license number to support@statmodel.coml
 Bengt O. Muthen posted on Thursday, November 16, 2017 - 3:32 pm
You may want to analyze this instead in long, twolevel format as shown in UG ex 9.16.
 Amber Fahey posted on Friday, November 17, 2017 - 12:44 pm
Thank you for responding so quickly! I am new to Mplus and growth modeling so I apologize for the following question, but what is the advantage to analyzing it in the long format vs the wide as I had been doing?
 Bengt O. Muthen posted on Friday, November 17, 2017 - 1:24 pm
Long format allows you to analyze much longer longitudinal data than wide can handle. But wide gives more flexible modeling.
 Amber Fahey posted on Wednesday, November 22, 2017 - 10:49 am
Thank you for your prompt response. Will the UG ex. 9.16 work without a covariate? I can't seem to figure out how to run it as an unconditional model, and not specifying anything in the Between = and %between% commands.
 Bengt O. Muthen posted on Wednesday, November 22, 2017 - 10:57 am
Yes.

Send your output to Support along with your license number.
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