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From | Maarten Buis <maartenlbuis@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: Goodness of fit for discrete hazard model with unobserved heterogeneity |
Date | Mon, 4 Jul 2011 09:45:13 +0200 |
On Sun, Jul 3, 2011 at 6:35 PM, Urmi Bhattacharya wrote: > I am estimating a discrete hazard model with unobserved heterogeneity > ( which is statistically significant). Is there any test for goodness > of fit for such a model? I generated the fitted survival function and > compared it with the sample survivor function but it is hardly > satisfactory because a) using the below model I get a predicted hazard > which assumes that the random effect is 0 and If you use -xtmelogit- instead of -xtlogit- you can estimate exactly the same model, but afterwards you can also predict the random effects. Together with the predicted linear predictor you can turn these into individual level probabilities. > b) It is only a visual comparison and hence not very convincing. I could not disagree more. When it comes to checking models test are the most unconvincing pieces of evidence and graphs the most convincing. Think about what a model is: it is a simplification of reality. This is just another way of saying that models are wrong, useful but wrong. So we do not need to do any tests as we already know the answer: We should reject the null hypothesis and if we don't our sample is just too small. The real issue with choosing models is to find the balance between simplicity and realism. This is a judgement call, where graphs are excellent tools to help you make those decisions and document them so you can explain your reasons to others. Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/