How to measure goodness of fit of a Hierarchical Bayes Model

[ahoeweler]

Hi everyone,

If I run e.g. a conditional logit model with proc phreg I get the standard error, the p value of the coefficients and the log likehihood as a general goodness of fit measure for the conditional logit model.
However, if I want to run a hierarchical Bayes model with only random effects with BCHOICE, I get the standard deviation and the 95% HPD Interval but no p-values and no standard errors in the summary output.

So my question is what are the best goodness of fit measures for the hierarchical Bayes model and how can I calculate them in an easy way in SAS?

Thank you very much for your help.

Best,

Alex

[ahoeweler]

Hi Rick,

for some reason, I get a notification that you replied to my question but I wouldn't see it in the actual post.

Has anyone the same problem?

Thank you for your help.

Best,

Alex

[Rick_SAS]

Sorry for the confusion.  I did not reply to your question. I moved your question into the Statistical Community and sent you a notifice that I did so.

[ahoeweler]

It might be still interesting for other readers so I just wanted to let you know that I found out that using the deviance information criterion (DIC) to account for the overall fit of the hierarchical Bayes model. To account for the fit of the individual estimators stating how much the mean estimates deviate from zero taking into consideration their standard deviations seems to be a good way.

Best,
Alex