[R] analysis of data with observation weights

Peter Dalgaard BSA p.dalgaard at biostat.ku.dk
Thu Nov 14 23:48:37 CET 2002

Michal Bojanowski <bojaniss at poczta.onet.pl> writes:

> I'm gettin the same coefficients, but different standard errors. I guess this is
> what you had in mind.
> I guess I need a book on WLS... Thank you for the answer anyway.

Thomas Lumley once did a brief but very good writeup on the various
kinds of weighting. I forget whether it was for one of the open
mailing lists or in connection with a discussion in R-core.

One thing I remember from it was the need to distinguish between the
various reasons for weighting. The one used in lm/glm is based on the
idea that some measurements are more precise than others and therefore
deserve more weight, so basically the weight is the inverse variance
of an observation. However, you might want to weight observations
differently even if their variance is the same, e.g. to obtain a
method that is stable against differences in population structure,
even if the model is slightly wrong. (Some rather subtle issues are
involved here and I'm not sure I'm representing them adequately.)

   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907
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