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RE: st: Multinomial Logit vs. Regression with dummy


From   SR Millis <srmillis@mindspring.com>
To   statalist@hsphsun2.harvard.edu
Subject   RE: st: Multinomial Logit vs. Regression with dummy
Date   Fri, 18 Jun 2004 06:54:20 -0700 (PDT)

Scott Menard's book, "applied logistic regression
analysis (2nd ed)" published by Sage provides an
excellent discussion of the potential limitations of
the multinomial logistic regression model---and
discusses alternatives.

SR Millis


--- Sugie Lee <sugie.lee@arch.gatech.edu> wrote:
> It seems like that -discrim- can only deal with a
> binary dependent
> variable(0/1).
> 
> .discrim CITY INDEP1 INDEP2 INDEP3 INDEP4
> 
> This command did not work because CITY has three
> groups (city A, city B,
> city C).
> 
> I looked at previous postings in the STATA Archive
> about discriminant
> analysis.
> I think we have two ado files for discriminant
> analysis: -discrim-
> and -daoneway-.
> But -daoneway- is not running on the STATA 8 of
> which I am using. It's for
> STATA 7.
> 
> Nick suggested multinomial logit analysis for this
> kind of case(see the
> below posting on Dec. 11th 2002).
> His suggestion seems like what I was supposed to do
> with multinomial logit
> analysis.
> 
> .mlogit CITY INDEP1 INDEP2 INDEP3 INDEP4
> 
> I agree that this approach is a little bit weird.
> But the result looks like what I expect.
> Is this approach seriously flawed?
> Any comment or better ideas?
> Thanks,
> 
> sugie
> 
> 
> 
> 
> 
> st: RE: discriminant function analysis
>
----------------------------------------------------------------------------
> ----
> From   "Nick Cox" <n.j.cox@durham.ac.uk>
> To   <statalist@hsphsun2.harvard.edu>
> Subject   st: RE: discriminant function analysis
> Date   Wed, 11 Dec 2002 23:01:53 -0000
>
----------------------------------------------------------------------------
> ----
> Sheela Athreya
> > Does anyone know if it is possible to perform the
> following
> > analysis on
> > STATA:
> >
> > I have a set of 35 fossils, from known taxonomic
> groups
> > (1,2,3).  There
> > are five measurements per fossil.  I then have a
> single
> > newly discovered
> > fossil, and want to find out how it will be
> classified
> > based on these
> > measurements.
> >
> > I wanted to use discriminant function analysis,
> but I'm not
> > sure if a)
> > that is the right approach, and b) how I can do it
> using the command
> > -discrim-, which requires that the grouping
> variable be
> > only 0/1, instead
> > of the three groups I have defined a priori.
> 
> 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.
> 
> Nick
> n.j.cox@durham.ac.uk
>
----------------------------------------------------------------------------
> ----
> 
> 
> 
> 
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu]On
> Behalf Of SR Millis
> Sent: Thursday, June 17, 2004 2:53 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: Multinomial Logit vs. Regression
> with dummy
> 
> 
> Another alternative is discriminant function
> analysis.
> 
> SR Millis
> 
> --- Sugie Lee <sugie.lee@arch.gatech.edu> 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:
> > .mlogit CITY POPDEN INDEP2 INDEP3 INDEP4
> >
> > 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.
> 
> CLIVE NICHOLAS        |t: 0(044)191 222 5969
> Politics              |e: clive.nicholas@ncl.ac.uk
> Newcastle University  |http://www.ncl.ac.uk/geps
> 
> *
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> 
> 
> 


=====
Scott R Millis, PhD, MEd, ABPP (CN & RP)
Director, Office of Clinical Trials
Kessler Medical Rehabilitation Research & Education Corp
1199 Pleasant Valley Way
West Orange, NJ  07052

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