I think it is likely I am missing something.  Here is a very simple example:

R code:

mat <- matrix(nrow = 10, ncol = 2, c(1,0,1,0,0,1,0,0,1,1),
c(5,4,1,6,3,6,5,3,7,9), dimnames = list(c(1,2,3,4,5,6,7,8,9,10),
c("column1","column2")))

g <- glm(mat[1:10] ~ mat[11:20], family = binomial (link = logit))

g$converged


SAS code:

data mat;
input col1 col2;
datalines;
1 5
0 4
1 1
0 6
0 3
1 6
0 5
0 3
1 7
1 9
;

proc logistic data=mat descending;
model col1 = col2 / link=logit;
run;

SAS output (in case you don't have access to SAS):
Convergence criterion satisfied

                  Estimate       SE
Intercept    -1.6118          1.7833
col2            0.3293          0.3383


Of course, with an example this small, it is not so surprising that the two
methods differ; and they hardly differ by a single S.  But as the datasets
get larger, the difference is more pronounced.  Let me know if you would
like me to send you a large dataset.  I get the feeling I am doing something
wrong in R, so please let me know what you think.

Thank you!

Ben Godlove

On Thu, Nov 11, 2010 at 1:59 PM, Albyn Jones <jones@reed.edu> wrote:

> do you have factors (categorical variables) in the model?  it could be
> just a parameterization difference.
>
> albyn
>
> On Thu, Nov 11, 2010 at 12:41:03PM -0500, Benjamin Godlove wrote:
> > Dear R developers,
> >
> > I have noticed a discrepancy between the coefficients returned by R's
> glm()
> > for logistic regression and SAS's PROC LOGISTIC.  I am using dist =
> binomial
> > and link = logit for both R and SAS.  I believe R uses IRLS whereas SAS
> uses
> > Fisher's scoring, but the difference is something like 100 SE on the
> > intercept.  What accounts for such a huge difference?
> >
> > Thank you for your time.
> >
> > Ben Godlove
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> --
> Albyn Jones
> Reed College
> jones@reed.edu
>
>

	[[alternative HTML version deleted]]

