On 11 Mar 2008 at 14:09, Rolf Turner wrote: > > It would appear that the SPSS procedure would then give exactly the same > point estimates of the parameters, and change the inference structure by > changing the ``denominator degrees of freedom'' from n-p to sum(w) - p. >
Well, if that IS what SPSS does, then it sounds like what Stata calls frequency weights, the general idea being that each "observation" in fact represents some non-negative number (w) of actual observations that have identical values. Not much more than a glorified version of a frequency distribution table. I don't see anything fundamentally wrong with frequency weights, given an appropriate situation. ---JRG John R. Gleason > This seems to me to make little sense ... But then, it ***is*** > SPSS. :-) > > cheers, > > Rolf > > On 11/03/2008, at 11:35 AM, Peter Dalgaard wrote: > > > Rolf Turner wrote: > >> On 11/03/2008, at 4:04 AM, Ben Domingue wrote: > >> > >> > >>> 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. > >> > >> > >> > > I believe case weighting in SPSS effectively replicates the > > relevant row (not sure if anything sensible comes out if weights > > are non-integer). So > > > > lm(...., data=mydata[rep(1:nrow(mydata),w),]) > > > > or thereabouts should do it. Might not be too efficient though. > > > > -- > > O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B > > c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K > > (*) \(*) -- University of Copenhagen Denmark Ph: (+45) > > 35327918 > > ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) > > 35327907 > > > > > > ###################################################################### > Attention: > This e-mail message is privileged and confidential. If you are not the > intended recipient please delete the message and notify the sender. > Any views or opinions presented are solely those of the author. > > This e-mail has been scanned and cleared by MailMarshal > www.marshalsoftware.com > ###################################################################### > > ______________________________________________ > 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. ______________________________________________ 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.
