Mimicking SPSS weighted least squares

Howdy,
In SPSS, there are 2 ways to weight a least squares regression:
1. You can do it from the regression menu.
2. You can set a global weight switch from the data menu.
These two options have no, in my experience, been equivalent.
Now, when I run lm in R with the weights= switch set accordingly, I
get the same set of results you would see with option #1 in SPSS.
Does anybody know how to duplicate option #2 from SPSS in R?

I think it's up to you to find out what ``option #2 from SPSS'' actually
*does*.  If you know that, then you can (with a modicum of effort)
duplicate that option in R.  The help file for lm() tells you that
R uses the weights by minimizing sum(w*e^2) where w = weights and
e = ``errors'' or residuals.

	cheers,

		Rolf Turner

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