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I’m using Mplus to conduct LCA with 3 categorical indicators (2 with 3 options and 1 with 2 options) and 5 continuous indicators. I am able to run a 2 and 4 class solution with no errors; however, when I attempt LCA with 3, 5, etc. classes I get the following 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 0.205D-20. PROBLEM INVOLVING PARAMETER 34. I’ve used tech1 to examine the parameter (an have an issues with C#2 parameter) and have changed start values, and yet this problem persist. Would you have any suggests on how I can ‘fix’ this issues? Additionally, what are your thoughts about having more classes than variables in the model? I welcome your comments. Thank you. |
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With two three-category variables and one binary variable, you have 17 degrees of freedom. You cannot have more than 17 parameters. |
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Hi Linda, Thank you! That makes sense. |
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lisa Car posted on Tuesday, April 16, 2019 - 6:13 pm
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Hello I am getting a similar response when running a 3 class LPA with 15 indicators. I have tried increasing starts to 100 20 without any change. The model terminates normally. Do you have any suggestions for how to rectify this? thank you! |
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We need to see your full output to answer this - send to Support along with your license number. |
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lisa Car posted on Monday, November 04, 2019 - 8:53 am
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Hello I am getting a similar error message running a 3 or 4 class LPA with 18 indicators. Increasing start values to 200 40 does not help. I also seem to be having another issue in that one of the parameter estimates in all 3 or 4 classes is negative and there are no negative values in the data. I am using -99 for missing and it is properly coded in the dataset for all variables and in Mplus. Thanks in advance for any help. |
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We need to see your output to be able to see what's going on - send to Support@statmodel.com including your license number. |
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