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is the error message for my CFA. I believe this means that my start values are inaccurate...does this mean that I need to provide better start values? If so, how can I change the start values? 


Please send your full output and license number to support@statmodel.com. 


Great, just sent it. Also, I have MPlus 6 installed on my Dell laptop. When I save output or input files, I'm not able to open them. I get an eror message that says the file "is not a valid Win32 application." Any suggestions? 


How are you opening those files? By doubleclicking on the files in Windows Explorer or by using the File Open menu option in the Mplus Editor? 


Dear Prof. Dr. Muthen, When I do a CFA, I get "No convergence. Number of iterations exceeded". I tried to change the starting values and the number of iterations, but it doesn't work... Do you have any suggestions? Thank you very much, Elien 


Try freeing the first factor loading of each factor and fixing the factor variances to one. It may be that the first factor loading which is fixed to one as the default would not be estimated close to one or is negative. f BY y1* y2 y3 y4; f@1; 


Thank you so much! The suggestion worked when I let all the second factor loadings free (not the first). But the fit is not good... I suppose this has to do with the model and is not changeable? However, maybe the fit will be better when the following problem is solved: "WARNING: THE RESIDUAL COVARIANCE MATRIX (THETA) IS NOT POSITIVE DEFINITE.THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO OBSERVED VARIABLES. CHECK THE RESULTS SECTION FOR MORE INFORMATION.PROBLEM INVOLVING VARIABLE ES." Thank you very much! 


Please send the output and your license number to support@statmodel.com. 

John Perry posted on Wednesday, September 19, 2012  3:57 pm



Hi Linda, in terms of nonconvergence, would I be right in assuming that this is probably because of bad starting values? If so, is it wise to see what starting values are and then perhaps identify very high ones and constrain these to one in the model? I've got a couple of models to converge by doing this but would like your advice. Many thanks, John 


I would not think that starting values is a big problem. We have good default starting values. Often it can be related to large variances so we recommend keeping variances of continuous variables between one and ten. It can also be caused by variances or residual variances approaching zero. If you have a problem, send it and your license number to support@statmodel.com. I do not think constraining values even if it works is a good idea. 


Dear Linda, I too am having some issues in getting convergence in a multi group CFA, and receive the message: NO CONVERGENCE. NUMBER OF ITERATIONS EXCEEDED. FACTOR SCORES WILL NOT BE COMPUTED DUE TO NONCONVERGENCE OR NONIDENTIFIED MODEL. I am trying to test the equivalency, or invariance, of the proposed baseline model (model 1) across the several groups. thanks, Mathew 


As a first step, run each group separately to see if you have convergence problems there. 


hi Linda, thank you for the advice. I ran each group separately, and had no convergence problems there. Some models are better than others (these are different data across different years), but all are good or exceptional fits. What would you suggest as a next step? regards Mathew 


Send the output of the multiple group analysis along with your license number to support@statmodel.com. 

benedetta posted on Sunday, May 24, 2015  9:34 am



Dear professors, I am running a second order CFA as below MODEL: I BY i1*i19; I@1; A by a1*a20; A@1; P BY p1*p11; SIGHT by i3* i4 i5; SIGHT@1; SIGHT with A @0; SIGHT with P @0; SIGHT with I @0; D BY I* A P ; D@1; D with sight@0; And I replicated the analysis using the data of two waves of my survey. The model is identified in one case but it does not converge when I replicate the analysis for the second wave. In particular I get this message: THE STANDARD ERRORS OF THE MODEL PARAMETER ESTIMATES COULD NOT BE COMPUTED. THE MODEL MAY NOT BE IDENTIFIED. CHECK YOUR MODEL. PROBLEM INVOLVING THE FOLLOWING PARAMETER: Parameter 135, D BY A THE CONDITION NUMBER IS 0.151D10. FACTOR SCORES WILL NOT BE COMPUTED DUE TO NONCONVERGENCE OR NONIDENTIFIED MODEL. Do you have an idea why this is happening? Thank you very much in advance 


Please send the output and your license number to support@statmodel.com. 

Marianne SB posted on Saturday, August 15, 2015  9:01 am



Hi Linda, I am trying to create a developmental measurement model with some shifting indicators of the same latent variable over time. Configural and metric invariance models run OK, but the scalar invariance model lead to convergence problems: NO CONVERGENCE. NUMBER OF ITERATIONS EXCEEDED. I have rescaled the variables so the residual variances are between 0 and 10, but this did not resolve the problem. Neither did increasing the number of iterations. Do you have any suggestions on how this might be resolved? Can it be a problem that the response categories for the items are on a categorical scale (aka: 0 = no, 3 = sometimes, and 6 = yes). I have used the MLR estimator, but the same happens when using the WLSMV estimator. 


We need to see the output to say. Send to support along with your license number. 

Marianne SB posted on Monday, August 17, 2015  7:12 am



Thank you for offering support. However, I did some more thinking and analyses and found out that the model was not identified. A simpler model resolved the issues. 

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