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[no subject]

With two categories discriminant analysis
is typically inferior to logit, but as
you have three, this sounds much more like -mlogit-
in Stata [sic]. However, I yield to experts here.


-----Original Message-----
[]On Behalf Of SR Millis
Sent: Thursday, June 17, 2004 2:53 PM
Subject: Re: st: Multinomial Logit vs. Regression with dummy

Another alternative is discriminant function analysis.

SR Millis

--- Sugie Lee <> wrote:
> Hello!
> I want someone to help me on a following question.
> Let's suppose we have three cities (city A, city B,
> city C).
> And we have just one variable which is population
> density(POPDEN)
> I may try regular regression as follows:
> .reg POPDEN dummy(city A) dummy(city B)
> What if I use multinomial logit?
> In this case, the dependent variable is
> "CITY"(A,B,C)
> .mlogit CITY POPDEN
> .listcoef
> I want to see differences of population density
> between cities.
> "listcoef" command immediately after "mlogit" will
> give me these
> differences.
> My question is whether I can use mlogit for this
> case?
> If mlogit is possible for this case, I will do
> analysis with more
> independent variables as follows:
> Any comments and suggestions will be helpful to me.
> Thanks.
> Sugie

Not if your real research question is "what affects population density?",
which I suspect is what you really want to ask. If so, using -mlogit- with
cities as the dependent variable strikes me as a bizarre approach: asking
the question "does density affect the probability of a city being a city
(or being the city that it actually is)" makes little sense, to me at
least. In my opinion, the OLS formulation you provided is much more
sensible, so try that and work from there.

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