BIC vs. Sample-size adjusted BIC for ... PreviousNext
Mplus Discussion > Latent Variable Mixture Modeling >
 cheng hong posted on Sunday, February 21, 2016 - 12:48 pm
I'm comparing a model with only main effects with a model with both main effects and two interactions. Since mPlus doesn't give me model fit information for interaction model except AIC and BIC, I compare these two models based on AIC and BIC.

But my problem is: for AIC, the moderation model fits better; for BIC, it fits worse. However, the result of sample-size adjusted BIC is consistent with AIC, indicating the model with interactions is better. In this case, can I go by the SA BIC?

My sample size is 482 and there are significant interactions.
 Bengt O. Muthen posted on Monday, February 22, 2016 - 5:58 pm
You can use compare the models using a likelihood-ratio chi-2 difference test. All you need are the loglikelihoods.
 cheng hong posted on Tuesday, February 23, 2016 - 6:45 pm
Thank you so much for your response!!

I tried to use likelihood-ratio, but the problem is I couldn't find scaling correction factor for my model with only main effects. Below are my results, can you take a look at it?

Model with both main effects and interactions:

Number of Free Parameters 138

H0 Value= -24946.434
H0 Scaling Correction Factor = 1.721 for MLR

Information Criteria

Akaike (AIC)= 50168.868
Bayesian (BIC)= 50745.424
Sample-Size Adjusted BIC= 50307.424
(n* = (n + 2) / 24)

Model with only main effects:

Number of Free Parameters = 132

H0 Value=-24957.359
H1 Value=-23840.497

Information Criteria
Akaike (AIC)= 50178.718
Bayesian (BIC)= 50730.207
Sample-Size Adjusted BIC=50311.250
(n* = (n + 2) / 24)

Thank you so much!!!
 Bengt O. Muthen posted on Wednesday, February 24, 2016 - 4:49 pm
Please send the two outputs to Support along with your license number.
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