Prof Brian Ripley <[EMAIL PROTECTED]> 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 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 ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
