[R] Multinomial logistic regression under R and Stata
Tak Wing Chan
tw.chan at sociology.oxford.ac.uk
Thu Mar 27 11:32:28 CET 2003
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:
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:
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.
Department of Sociology, University of Oxford,
Littlegate House, St Ebbes, Oxford OX1 1PT, UK
tel: +44 (1865) 286176, fax: +44 (1865) 286171
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