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Mplus Discussion > Latent Variable Mixture Modeling >
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 Kiki Yang posted on Saturday, August 20, 2005 - 4:15 am
Hello!
This is my output. I would like to know does the "Pearson Chi-Square Value" of "Chi-Square Test of Model Fit for the Binary and Ordered Categorical (Ordinal) Outcomes" mean overall or other?
My English is poor. I hope you can understand my question.


TESTS OF MODEL FIT

Loglikelihood

H0 Value -5736.266

Information Criteria

Number of Free Parameters 27
Akaike (AIC) 11526.531
Bayesian (BIC) 11642.102
Sample-Size Adjusted BIC 11556.395
(n* = (n + 2) / 24)
Entropy 0.883

Chi-Square Test of Model Fit for the Binary and Ordered Categorical
(Ordinal) Outcomes

Pearson Chi-Square

Value 0.001
Degrees of freedom cannot be computed for this model part.

Likelihood Ratio Chi-Square

Value 0.001
Degrees of freedom cannot be computed for this model part.
 Linda K. Muthen posted on Saturday, August 20, 2005 - 9:19 am
These two tests are for the latent class indicators only. They are not for the full model.
 Kiki Yang posted on Saturday, August 20, 2005 - 4:55 pm
Thank you for your respond.
I want to be sure again.
Is the P value test for the latent class indicators or categorical observed variables?
 bmuthen posted on Sunday, August 21, 2005 - 1:37 pm
The p value test is for the latent class indicators, which are the categorical observed variables.
 Kiki Yang posted on Sunday, August 21, 2005 - 4:23 pm
Thank you very much for your help.
 Reid Offringa posted on Monday, October 28, 2013 - 2:35 pm
Hello everyone,

I'm trying to run a latent class analysis with four continuous variables and two categorical variables. I keep getting an error stating that the degrees of freedom cannot be calculated. As a result, I do not have enough information to assess the model fit. Do you have any suggestions?


Here is a sample of the relevant output:

MODEL FIT INFORMATION

Number of Free Parameters 24

Loglikelihood

H0 Value -985.151
H0 Scaling Correction Factor 1.123
for MLR

Information Criteria

Akaike (AIC) 2018.301
Bayesian (BIC) 2098.053
Sample-Size Adjusted BIC 2022.013
(n* = (n + 2) / 24)

Chi-Square Test of Model Fit for the Binary and Ordered Categorical
(Ordinal) Outcomes

Pearson Chi-Square

Value 1.455
Degrees of freedom cannot be computed for this model part.

Likelihood Ratio Chi-Square

Value 1.322
Degrees of freedom cannot be computed for this model part.
 Linda K. Muthen posted on Monday, October 28, 2013 - 4:41 pm
These tests are not overall tests of model fit. They test only the observed versus expected frequency tables for the categorical latent class indicators. Absolute fit statistics are not available with categorical variables and maximum likelihood estimation. Nested models can be compared using -2 times the loglikelihood difference which is distributed as chi-square.
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