Re: st: collecting interaction terms after estimation

[Maria Ana Vitorino <vitorino@wharton.upenn.edu>]

Dear Richard,
Thanks for your suggestions.
I'm actually using asclogit and it seems that factor variables and  
time series operators are not allowed...
Ana


On Nov 5, 2011, at 2:20 PM, Richard Williams wrote:

> At 11:48 AM 11/5/2011, Maria Ana Vitorino wrote:
> > Dear statalist users,
> > Suppose I have the following model in which I regress people's
> > decision to buy or not to buy something on people's characteristics
> > interacted with distance.
> > (the Xs refer to interactions between distance to the store and
> > other people's characteristics).
> >
> > logit choice dist dist2 ageXdist sexXdist incXdist
> If you have Stata 11 or 12, you are making this too hard. Use factor  
> variable notation instead.
> clonevar xdist = dist
> logit choice i.sex xdist age inc c.xdist#c.xdist c.age#c.xdist  
> i.sex#c.xdist c.inc#c.xdist
> Follow that up with
>
> replace xdist = 10 if !missing(xdist)
> predict p1, p
>
> Change the last line to
>
> predict p1, p if e(sample)
>
> if you only want to use the same cases that were used in the  
> estimation.
> Then,
>
> drop xdist
> clonevar xdist = dist
> [repeat process with remaining models; call predictions p2, p3, or  
> whatever)
> Note that you run the logistic regressions using the original values  
> of distance. You then set distance = 10 and do your predictions. By  
> using the factor variable notation, Stata will understand how the  
> value of distance affects both the squared term and the interaction  
> terms.
> Also note that in your original example you did not have the main  
> effects of sex, age, income or inc. I have added them, but if for  
> some reason you really really really don't want them you should drop  
> the main effects from the model.
> If you are condemned to using Stata 10 or earlier, you will need to  
> tweak the approach so that you run the regression, and then  
> recompute all the terms setting distance to 10 and then doing the  
> prediction.
>
> > And I would like to obtain predicted probabilities for each person
> > when distance is set to 10.
> >
> > This would be easy enough if I only had this model specification. But
> > I have several possible models (and may keep adding and changing the
> > current ones).
> >
> > This is what I have so far:
> >
> >
> > local chars "sex age inc"
> > foreach varname in `chars'{
> >        gen distX`varname' = dist*`varname'
> > }
> > gen dist2= dist*dist
> >
> > *model 1
> > logit choice dist dist2 ageXdist sexXdist incXdist
> >
> > *model 2
> > logit choice dist dist2  sexXdist incXdist
> >
> > *model 3
> > logit choice dist ageXdist  incXdist
> >
> > My question is then: Is it possible to write code general enough that
> > would calculate predicted probabilities for when distance is set to  
> > 10
> > for *any* of the above models?
> >
> >
> > Any insights are appreciated.
> > Thanks,
> > Ana
> > *
> > *   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/
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> HOME:   (574)289-5227
> EMAIL:  Richard.A.Williams.5@ND.Edu
> WWW:    http://www.nd.edu/~rwilliam
>
> *
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