Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: xtnbreg - robusteness check and model relevance

From   Simon Falck <>
To   "" <>
Subject   st: xtnbreg - robusteness check and model relevance
Date   Thu, 10 Jan 2013 10:34:58 +0000

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,

*   For searches and help try:

© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index