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In Nylund et al. (2007) on deciding the number of classes in mixture models, the results indicate that, in general, BIC is better than AIC. However, I am wondering if anyone can interpret why AIC performs better than BIC when the LCA has categorical outcomes, small sample size, and unequal class sizes. |
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Not sure. Anyone? Somehow it must relate to the fact that AIC does not punish models with many parameters as much as BIC does. |
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I suppose I'd also like to know why BIC performs better than AIC when the LCA has continuous outcomes and why BIC performs better than AIC when the LCA has categorical outcomes, small sample size, and equal class sizes too. Thanks! |
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Not sure if anyone knows that. |
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