Dear Brian,
Estimating seperate logistic regressions for each group is equivalent
of estimating a single logistic regresion with dummy variables for
each group and interactionterms of each group dummy with all other
explanatory variables. So the `seperate logistic regression model' is
larger (uses more degrees of freedom) than only adding the dummies
for group membership.
Maarten
--- In [email protected], brian.h.nathanson@a... wrote:
> Dear Stata Users,
> I'm creating a logistic regression model with many dichotomous
variables along with one term that has 8 categories coded 1,2,..8. I
can create 7 dummy variables and have a very large model. Would it
be legitimate if my sample sizes are large enough to create 8
separate models with each model representing one subgroup? Can
anyone comment on the pros and cons of using dummy variables versus
creating separate "subgroup" models based on the remaining
independent variables? Thanks!
> -Brian
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