Non-Convergence PreviousNext
Mplus Discussion > Confirmatory Factor Analysis >
Message/Author
 anonymous posted on Friday, June 23, 2006 - 4:26 pm
My data is not converging despite lowering my criterion and increasing the number of iterations. What should I do next?
 Linda K. Muthen posted on Friday, June 23, 2006 - 5:07 pm
There are some suggestions in the user's guide under the topic non-convergence. If they don't help, send your input, data, output, and license number to support@statmodel.com.
 Andreas Richter posted on Thursday, June 17, 2010 - 2:13 pm
Dear Mplus team, I would like to run a 1-factor model (CFA) with my data (n=177) for the only reason to reject that model - but the model doesn't run. I get the following error: NO CONVERGENCE. NUMBER OF ITERATIONS EXCEEDED

Could you help me please?
 Linda K. Muthen posted on Thursday, June 17, 2010 - 3:00 pm
Please send your output and license number to support@statmodel.com.
 Pauline Aarten posted on Tuesday, July 30, 2013 - 10:16 am
Dear Mplus team,

I have collected data on two different time points. Unfortunately, my N is quite low (n=95 per time point). During a SEM course the teacher suggested that I should do multiple group analysis so I can take the two time points in my model and see if my respondents differ in their answers over time. I tried running my CFA model with my data (n=190) using the grouping variable. However, I get the following error: 'No convergence. Number of iterations exceeded'. I have increased the number of iterations to 50,000 and it still won't converge.

Could you please help me with this?
 Bengt O. Muthen posted on Tuesday, July 30, 2013 - 11:40 am
I assume that you have different subjects at the two time points so that multiple-group analysis is relevant. As a first step to solve your non-convergence problem you should analyze each group separately. And if that is problematic, switch to EFA.

If this doesn't help, you need to send your output, input, data, and license number to support@statmodel.com.
 Eiko Fried posted on Monday, June 15, 2015 - 10:50 am
Hi.

We're running a longitudinal measurement invariance model, 2 timepoints, 28 indicators, 3 EFA factors, WLSMV estimator.

We allow for correlated item residuals across time
(x1_t1-x28_t1 PWITH x1_t2-x28_t2),
seeing that otherwise modindices show massive misfit, and that it seems to be recommend in the literature.

M1 baseline, M3 strong (thresholds), and M4 strict (residual variances) models converge fine without problems (and fit a lot better than not allowing item residuals to be correlated). Only M3 strong invariance model (loadings) does not converge:

NO CONVERGENCE. SERIOUS PROBLEMS IN ITERATIONS. CHECK YOUR DATA, STARTING VALUES AND MODEL.

Why could that be? (cannot really post the output seeing that is it way too long)

Thank you
EF
 Linda K. Muthen posted on Monday, June 15, 2015 - 12:22 pm
If you have not already done so, you should fit the model at each time point as a first step. The same model should fit well at each time point before you test for measurement invariance.
 Eiko Fried posted on Monday, June 15, 2015 - 12:31 pm
Thanks Linda. When we originally tried the CFA framework, the CFA model we derive from the baseline measurement point does not fit well to the follow up time point.

This is why we decided to use the EFA/ESEM framework instead, to which my question refers.

Therefore I'm not sure what you mean——since we are using an ESEM approach, the EFA model fits equally well (because it's completely free) to both measurement points (although the parallel analysis suggests 4 factors at baseline and only 3 at follow up)
 Linda K. Muthen posted on Monday, June 15, 2015 - 3:07 pm
If you do not find at a minimum the same number of factors at each time point, you cannot test for measurement invariance across time.
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: