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From |
"Michael I. Lichter" <mlichter@buffalo.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: MLOGIT versus a set of LOGIT models [re-posting] |

Date |
Wed, 19 Aug 2009 11:14:45 -0400 |

Jon Heron wrote:

Thanks Kieran, I was beginning to think that the difference lay between continuous and categorical predictors - i had shown that a model with a 4-level categorical predictor could be factored into logits, whilst treating the same variable as continuous meant that this was not possible. I now see that including *two* categorical predictors also results in the logits giving a different answer. Hence it does appear to be model complexity rather than variable type. I have a Kleinbaum paper in front of me (IJE 26(6), pp1323-1333) but I will attempt to track down the book you mention. In the meantime I think I have learned enough to drop this from from my lecture as it is nothing more than a distraction. all the best, Jon On Tue, August 18, 2009 7:47 pm, Kieran McCaul wrote:Hi Jon, I think your belief may be wrong. I think that when you only have one binary predictor then the results from a multinomial logistic regression will agree with the results of a series of logistic regressions, but in more complex models this is not so. From memory (I haven't got the book with me) Kleinbaum & Klein discuss this. 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 email: Kieran.McCaul@uwa.edu.au http://myprofile.cos.com/mccaul http://www.researcherid.com/rid/B-8751-2008 ______________________________________________ If you live to be one hundred, you've got it made. Very few people die past that age - George Burns -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Jon Heron Sent: Wednesday, 19 August 2009 1:31 AM To: statalist@hsphsun2.harvard.edu 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 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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

-- Michael I. Lichter, Ph.D. <mlichter@buffalo.edu> Research Assistant Professor & NRSA Fellow UB Department of Family Medicine / Primary Care Research Institute UB Clinical Center, 462 Grider Street, Buffalo, NY 14215 Office: CC 126 / Phone: 716-898-4751 / FAX: 716-898-3536 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: MLOGIT versus a set of LOGIT models [re-posting]***From:*"Jon Heron" <Jon.Heron@bristol.ac.uk>

**st: RE: MLOGIT versus a set of LOGIT models [re-posting]***From:*"Kieran McCaul" <Kieran.McCaul@uwa.edu.au>

**Re: st: RE: MLOGIT versus a set of LOGIT models [re-posting]***From:*"Jon Heron" <Jon.Heron@bristol.ac.uk>

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