st: xtnbreg - robusteness check and model relevance

[Simon Falck <simon.falck@abe.kth.se>]

Dear Statalist, 

I am implementing a fixed effect count model for panel data using following commands:

xtset year id
xtnbreg dv $xlist, fe

My question is how to evaluate model relevance and how to make a robustness test?

The relevance or precision of a count model seems often to be described in terms of how close the predicted values are to the observed values, usually by comparing the distribution of probabilities of observed and predicted counts. However, from what I understand, it is not possible to use the command -prcounts- after -xtnbreg-, which is used after -nbreg- to derive predicted values. Any suggestions on what is a reasonable strategy in this case?

Thanks in advance,
/Simon

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