--- On Wed, 13/1/10, Rosenstock, Summer E. wrote:
> I would like to test whether adding an interaction term to
> my model makes the model an overall better fit. In the past
> with logistic regression I've used the log likelihood ratio
> test to see if there is added benefit by comparing the full
> model to the reduced model, but stata is not so keep to do
> this with xtgee.
Testing interactions in a non-linear model can be a
surprisingly complicated, if you are interested in marginal
effects, see e.g. (Norton et al. 2004). However, things
are much easier if you want to remain within the odds ratio
or risk ratio metric. In your case you can then estimated
the model with interactions and use
-testnl exp(_b[interaction])=1- to test the interaction
effect (where "interaction" is the name of your interaction
variable).
Here is a recent post about the difference between the two:
http://www.stata.com/statalist/archive/2010-01/msg00276.html
> I'm having to use logit in some cases because not
> all of my log-binomial models will converge, which is super
> frustrating...but that's another topic.
I posted an alternative solution to that problem recently:
http://www.stata.com/statalist/archive/2010-01/msg00182.html
Hope this helps,
Maarten
Edward C. Norton, Hua Wang and Chunrong Ai (2004) Computing
interaction effects and standard errors in logit and probit
models. The Stata Journal, 4(2): 154--167.
http://www.stata-journal.com/article.html?article=st0063
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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