I was messing around with some data in R and SAS (the reason is
unimportant) fitting a multiple linear regression and got a
curious discrepancy.  The data set is too big to post, but if
someone wants it, I can send it.

So, here are the (partial) results:

From R:

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) 61.11434    1.48065  41.275  < 2e-16 ***
sexWomen     2.91108    0.35753   8.142    5e-16 ***
diabp        0.20675    0.01504  13.746  < 2e-16 ***
age         -0.08085    0.02088  -3.871 0.000110 ***

From SAS (sorry about word-wrap if it happens):

                              Parameter Estimates

                                                Parameter     Standard
Variable Label DF Estimate Error t Value

Intercept Intercept 1 58.20326 1.57802 36.88 SEX SEX 1 2.91108 0.35753 8.14 DIABP Diastolic BP mmHg 1 0.20675 0.01504 13.75 AGE Age (years) at examination 1 -0.08085 0.02088 -3.87

                              Parameter Estimates

             Variable   Label                         DF  Pr > |t|

             Intercept  Intercept                      1    <.0001
             SEX        SEX                            1    <.0001
             DIABP      Diastolic BP mmHg              1    <.0001
             AGE        Age (years) at examination     1    0.0001

The curious thihs is that all parameter estimates agree except the
intercept.  In R I also computed the coefficients directly using
(X'X)^(-1) X' y and get the same coefficients as lm() have me.
Also, ols() in Design agrees with lm()

As far as I can tell, the data used in R and SAS are identical.  So,
whose answer is correct and how do I prove it?  Here's my sessionInfo
(yes, I know my version of R is oldish).

> sessionInfo()
R version 2.8.0 (2008-10-20)
i686-pc-linux-gnu

locale:
LC_CTYPE=en_US;LC_NUMERIC=C;LC_TIME=en_US;LC_COLLATE=C;LC_MONETARY=C;LC_MESSAGES=en_US;LC_PAPER=en_US;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US;LC_IDENTIFICATION=C

attached base packages:
[1] splines   stats     graphics  grDevices utils     datasets  methods
[8] base

other attached packages:
[1] Design_2.2-0    survival_2.35-4 Hmisc_3.6-0     lattice_0.17-25

loaded via a namespace (and not attached):
[1] cluster_1.12.0 grid_2.8.0

--
Kevin E. Thorpe
Biostatistician/Trialist, Knowledge Translation Program
Assistant Professor, Dalla Lana School of Public Health
University of Toronto
email: kevin.tho...@utoronto.ca  Tel: 416.864.5776  Fax: 416.864.3016

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