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Re: st: Using mixlogit as a substitute of xtlogit.
From
Maarten buis <[email protected]>
To
[email protected]
Subject
Re: st: Using mixlogit as a substitute of xtlogit.
Date
Fri, 4 Jun 2010 01:31:22 -0700 (PDT)
--- On Fri, 4/6/10, ippab ippab wrote:
> I am wondering if there is any benefit of using mixlogit
> for a binary dependent variable in a panel data.
> Basically, to use mixlogit, I will have to create two
> alternatives (which are complementary), an alternative
> specific constant, and interactions between independent
> variables and the alternative specific constant. Is
> this is a wise thing to do?
No, you should get very similar results, and the differences
are due to particularities of the maximizing algorithms, so
have no substantive interpretation.
> My vague understanding is that mixlogit allows for more
> heterogeneity than xtlogit.
Not true, the value of -mixlogit- is that it allows one to
estimate a random effects model within a multinomial logit.
> But, I am confused about interpreting a population average
> beta obtained from xtlogit in light of estimates from
> mixlogit. Just to give an example, if the estimate
> for x1 is 2.05 from xtlogit, the interpretation would be
> that increasing x1 increases the the likelihood of y=1.
> Now, getting a similar estimate from mixlogit, e.g., mean
> is 2.5 for x1 with std 3.10, makes the interpretation
> complicated. This means for about 20.9% of the sample,
> increasing x1 does not increase the likelihood of
> y=1. Am I understanding these correctly?
Yup, and now it is more clear to me why you are comparing
with -mixlogit-. I guess that you were interested in making
some of the coefficients random as well. If that is the case
then you should have used -xtmelogit- instead.
> The more critical question is, if more than 20% or 30% of
> the sample have different preference, what does it mean to
> have a positive significant coefficient (mean)?
It means that people behave differently to the same stimulus,
but that on average the effect is positive. A possible next
step would be to try to explain this variation by adding
interactions between higher level variables and the lower
level variable x1.
Hope this helps,
Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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