From p.dalgaard at biostat.ku.dk  Fri May 26 17:11:47 2006
From: p.dalgaard at biostat.ku.dk (Peter Dalgaard)
Date: 26 May 2006 17:11:47 +0200
Subject: [Rd] (PR#8877) predict.lm does not have a weights argument for
In-Reply-To: <Pine.LNX.4.64.0605240918180.9937@gannet.stats.ox.ac.uk>
References: <20060524053520.1ABA5CD41@slim.kubism.ku.dk>
	<x2k68bdelc.fsf@viggo.kubism.ku.dk>
	<Pine.LNX.4.64.0605240918180.9937@gannet.stats.ox.ac.uk>
Message-ID: <x2lkso253g.fsf@turmalin.kubism.ku.dk>

Prof Brian Ripley <ripley at stats.ox.ac.uk> writes:

> > (e) Inverse probability weights: Knowing that part of the population
> > is undersampled and wanting results that are compatible with what you
> > would have gotten in a balanced sample. Prototypically: You sample X,
> > taking only a third of those with X > c; find population mean of X,
> > (or univariate regression on some other variable, which is only
> > recorded in the subsample).
> 
> I would call this an example of case weights (you are just weighting
> cases and saying `I have 1/p like this', and in rlm there is a
> difference between (a) and (b) and you would want to use
> wt.method="case" for (e)).

No it's not quite the same. One is "I have 3 of these", the other is
"I have looked at one case, but it comes from a population that I know
is undersampled by a factor of 3". Standard error of estimates will be
considerably different.

-- 
   O__  ---- Peter Dalgaard             ?ster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark          Ph:  (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)                  FAX: (+45) 35327907



[Rd] (PR#8877) predict.lm does not have a weights argument for
Peter Dalgaard