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| Model fit indices with count outcome |
 
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| Xiang Liu posted on Friday, May 06, 2016 - 7:39 am
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| Hi, I am modeling count outcome using a negative binomial regression on one latent factor and several observed covariates. It seems that besides the AIC and BIC, Mplus doesn't provide any absolute mode fit index. Any suggestions? Thanks! |
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| Chi-square and related fit statistics are not available for this model. In this case, nested models can be compared using -2 times the loglikelihood difference which is distributed as chi-square. Non-nested models with the same set of dependent variables can be compared using BIC. |
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| BL posted on Wednesday, September 18, 2019 - 1:36 pm
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I've estimated a model with 1 predictor, 3 mediators, and 2 latent outcome variables (Y1, Y2); Y2 is informed by 4 manifest count variables (nb). I thought chi-square fit would not be generated because the unit of the latent outcome variable is a count, but several chi-square indices were calculated. Are these valid for describing absolute fit? If so, can you clarify about which is most appropriate to report?
Chi-Square Test of Model Fit for the Count Outcomes**
Pearson Chi-Square
Value 2547.717
Degrees of Freedom 7973
P-Value 1.0000
Likelihood Ratio Chi-Square
Value 1029.021
Degrees of Freedom 7973
P-Value 1.0000
Chi-Square Test for MCAR under the Unrestricted Latent Class Indicator Model
for the Count Outcomes
Pearson Chi-Square
Value 25.589
Degrees of Freedom 799
P-Value 1.0000
Likelihood Ratio Chi-Square
Value 6.937
Degrees of Freedom 799
P-Value 1.0000 |
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| No, these are not overall tests of model fit. Such a test has not been developed. |
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