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st: MLOGIT versus a set of LOGIT models [re-posting]


From   "Jon Heron" <Jon.Heron@bristol.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: MLOGIT versus a set of LOGIT models [re-posting]
Date   Tue, 18 Aug 2009 18:30:38 +0100 (BST)

 Re-posted following a reading of the relevant FAQ



 Dear Statalisters,


  (I am using Stata/MP v10.1, born 02 Feb 2009)

 It was my belief that the regression estimates from a multinomial logistic
 regression model -mlogit- could be replicated through a set of simple logit
 models with the appropriately derived binary outcomes.

 Whilst attempting to demonstrate this fact for some teaching material on
 polytomous IRT that i am writing, I moved from my usual categorical
 predictors to a continuous covariate + discovered that the above equivalence
 no longer held.

 for instance, with a 4-level outcome (ghq1)  and either a binary predictor
 (ghq3_bin) or a 4-level predictor treated as a continuous variable (ghq3),
 I fitted models with the two commands

 ******************************
 mlogit ghq1 ghq3_bin, baseoutcome(0)
 mlogit ghq1 ghq3, baseoutcome(0)
 ******************************

 the former can be replicated using logits, whilst the latter cannot.
 I am struggling to understand why this should be.


 I would very much appreciate any advice you can give,




 Jon
-- 
Dr Jon Heron
ALSPAC Stats Team Leader
Department of Social Medicine
University of Bristol
Oakfield House
Oakfield Grove
Bristol
BS8 2BN


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