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Kleinbaum DG and Klein M (2005). Logistic Regression: A Self-Learning
Text. 2nd Ed.  Springer.

Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2701
Fax: (08) 9224 8009
If you live to be one hundred, you've got it made.
Very few people die past that age - George Burns

-----Original Message-----
[] On Behalf Of Jon Heron
Sent: Wednesday, 19 August 2009 1:31 AM
Subject: st: MLOGIT versus a set of LOGIT models [re-posting]

 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
 regression model -mlogit- could be replicated through a set of simple
 models with the appropriately derived binary outcomes.

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

 for instance, with a 4-level outcome (ghq1)  and either a binary
 (ghq3_bin) or a 4-level predictor treated as a continuous variable
 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,

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

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