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Re: st: xtlogit postestimation with predict


From   Dave Ohls <[email protected]>
To   [email protected]
Subject   Re: st: xtlogit postestimation with predict
Date   Tue, 9 Jul 2013 17:13:29 -0400

Sorry to not be clear: the question is why the two sets of predicted
probabilities are different, what each is reporting, and which (if
either) is correct.

There are quite a few individuals in the overall population that don't
change state (unit of analysis is interstate dyad-year, DV is war, so
many dyads never feature a war).  However, most of these are excluded
already by a restriction in the model specification (the -if CV3==1-),
and the rest are, as you say, dropped in estimating the main model.
How would this affect postestimation?

On Tue, Jul 9, 2013 at 4:34 PM, Richard Herron
<[email protected]> wrote:
> I don't really understand the question, but I will offer that panel
> logit with fixed effects is not the same as a logit model with
> indicator variables.
>
> To estimate the model there must be within individual variation in the
> dependent variable, so -xtlogit, fe- drops any individuals that don't
> change state.
>
> Do you have many individuals that don't change state?
>
> On Tue, Jul 9, 2013 at 3:27 PM, Dave Ohls <[email protected]> wrote:
>> I am getting inconsistent sets of results using the -predict- command
>> for postestimation predicted probabilities after -xtlogit- models.
>> I'm using Stata/IC 11.2 for Windows.
>>
>> I am estimating fixed effects logit models using code of the form:
>> -xtlogit DV IV1 IV2 CV1 CV2 if CV3==1, fe-
>> and want to interpret substantive results on continuous IV1 in terms
>> of predicted probabilities at different values.  Because effects are
>> non-linear and dependent on values of the FE/other vars, I'm
>> considering these within specific substantively-important cases.
>>
>> To do so, I create 5-10 dummy copies (labeled with a 1 in a variable
>> called dummy) of a particular case and delete the dependent variable
>> so as not to include it in the estimation of the model itself.  I keep
>> all variable values as they are in the real case, except altering IV1
>> to set it at its minimum for one of the copies, mean in another, max
>> in another, mean plus 1 SD in another, etc.  I then estimate the
>> model, followed by postestimation commands.
>>
>> The problem is that I get very different sets of results when I run:
>> -predict p1 if dummy==1-
>> than when I run:
>> -predict p2-
>> The numbers aren't the same even within those cases (dummy==1) where I
>> get a predicted probability in each.  I assume this is something to do
>> with how it handles the fixed effects, but I can't tell from the
>> manual/past forum topics/etc what it is, or which is correct.
>>
>> Also, I get a totally different (third) set of results when I run:
>> -predict p3, pu0-
>> Given info in the manual I interpret this set as the predicted
>> probabilities when the FEs are set to 0, which is not substantively
>> correct for what I'm trying to do - I include it here only to show
>> that that's not what's happening in either set of results above.
>>
>> I have tried replicating this on other datasets and can't get the same
>> inconsistency.  Any ideas?
>>
>> Thanks so much for your time.
>>
>> -Dave
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