[Limdep Nlogit List] Getting AIC, BIC and CAIC from a latent class model output

Fred Feinberg feinf at umich.edu
Wed Sep 24 00:09:59 EST 2008


They are very easy to calculate, and the formulas are Google-able. All you need is the number of parameters, the LL and the number of observations.  Here is a funny little guide to how to use and interpret them:

    http://www.cs.cmu.edu/~zhuxj/courseproject/aicbic/index.htm

Fred

immaculate omondi wrote:

> I am running some Latent class models. I would like to know how many segments (classes) would give me the best model fit. I understand that the information criteria statistics (Akaike Information Criterion- AIC, bayesian Information Criteria- BIC and CAIC) can be helpful, in part, in giving an indication of the fit of the model as the segments are added.
>
> However, the output results I get from my models does not give these information criteria statistics. How can I get them for my models? If not, is there another way of assessing the model fit as segments are added in a model?
>
> Thanks,
> Immaculate
>
>
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