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st: Multinomial logistic regression under R and Stata


From   Tak Wing Chan <tw.chan@sociology.oxford.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: Multinomial logistic regression under R and Stata
Date   Thu, 27 Mar 2003 11:09:14 +0000

Dear Colleagues

I have been fitting some multinomial logistic regression models using R (version 1.6.1 on a linux box) and Stata 7. Although the vast majority of the parameter estimates and standard errors I get from R are the same as those from Stata (given rounding errors and so on), there are a few estimates for the same model which are quite different. I would be most grateful if colleagues could advise me as to what might be causing this, and should I worry ...

Anyway, with R, I have been using the function multinom under the package nnet. Below are two examples where the estimates for standard error differ substantially between R and Stata:

beta s.e.
R: 5.939880 2.920165
Stata: 5.939747 5.455495

R: 11.228705 2.191625
Stata: 11.22761 4.630293

The parameters concerned are the quadratic term of a quantitative variable (measuring social status). I notice that the s.e. for this quadratic term are large anyway compared to other s.e. in the model.

There are other differences between R and Stata, and these concerned the intercept terms. Here is an example:

beta s.e.
R: 0.2870793 0.4512347
Stata: -0.2109653 0.5053566

Since both estimates are not significantly different from zero, I trust I can ignore the difference between the estimates. Or could I?

Many thanks in advance for any help. Please let me know if I should provide further info.

With best wishes. Wing

ps. I have posted this query to R-help already. But following the advice of a colleague, I am curious to know the views from colleagues in the Stata community ...

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tel: +44 (1865) 286176, fax: +44 (1865) 286171
http://users.ox.ac.uk/~sfos0006



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