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From |
Maarten buis <maartenbuis@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Suest with different estimators (logit & mlogit) |

Date |
Fri, 11 Feb 2011 11:07:46 +0000 (GMT) |

--- On Fri, 11/2/11, carola.degroot wrote: > I would love to use the suest command to test the > differences between the coefficients of two different > models. Although the sample of the models differ, > they partly overlap (the sample used in the second > model is a subselection of the sample used in the > first model). The first model is a logistic > regression model (logit), the second model is a > multinomial regression model (mlogit). So although > the models are completely the same with respect to > the independent variables, the dependent differs. > I've read that Suest allows for different estimators, > but my supervisor is worried that suest won't provide > "reliable" ("fair") results because it might not be > fair to compare the coefficients of a model with an > estimator with only 2 categories with a model with an > estimator with 3 categories. Unfortunately, I'm not > really an expert with the methodology behind the > suest command, nor is my supervisor. Therefore I'm > not sure whether this concern is indeed justified, > and whether it's necessary to change the dependent > of the second model into a binomial variable in > order to run a fair suest for the cross-model > comparison. This is not a matter of fairness and it is also not a matter of -suest-, it is a matter of comparing comparable stuff. -suest- will let you make that comparisson, question is does it mean anything? Lets say your mlogit model has for its dependent variable categories A, B, and C, and that A is the reference category. In that case the parameters in the first panel of the output have a dependent variable that is the logarithm of the expected number of Bs per A, while in the second panel the dependent variable is the logarithm of the expected number of Cs per A. Now assume your logit model only distinguishes between (A or B) and C. In that case the dependent variable is the logarithm of the expected number of Cs per (A or B). The parameters are obviously very different beasts, so it is hard to see how such a comparison can be meaningful. I see two options: often, you can, with a bit of creative derivation, find comparable contrasts. In that case you can use -suest- with -logit- and -mlogit- models, but your subsequent test commands will be complicated. Alternatively, you can turn your -mlogit- in a -logit- model by recoding the dependent variable such that they have the same meaning. A good introduction in -mlogit- and -logit- models is: J. Scott Long and Jeremy Freese (2006) "Regression Models for Categorical Dependent Variables Using Stata, 2nd Edition". College Station, TX: Stata Press. <http://www.stata-press.com/books/regmodcdvs.html> Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * 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/

**Follow-Ups**:**RE: st: Suest with different estimators (logit & mlogit)***From:*"Groot, de Carola" <Carola.deGroot@pbl.nl>

**References**:**st: Suest with different estimators (logit & mlogit)***From:*"carola.degroot" <carola.degroot@pbl.nl>

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