[R] Calculating/understanding variance-covariance matrix of logistic regression (lrm $var)
Martin Maechler
maechler at stat.math.ethz.ch
Thu Jan 29 09:22:31 CET 2004
>>>>> "Karl" == Karl Knoblick <karlknoblich at yahoo.de>
>>>>> on Thu, 29 Jan 2004 02:34:27 +0100 (CET) writes:
Karl> Hallo!
Karl> I want to understand / recalculate what is done to get
Karl> the CI of the logistic regression evaluated with lrm.
Karl> As far as I came back, my problem is the
Karl> variance-covariance matrix fit$var of the fit
Karl> (fit<-lrm(...), fit$var). Here what I found and where
Karl> I stucked:
Karl> -----------------
Karl> library(Design)
.....
The usual ("official") R (and S) way for this is using
r <- glm(..., family = binomial)
with predict(r, .., se.fit=TRUE)
and vcov(r)
giving the variance-covariance matrix,
calling the vcov.glm(.) method in this case, which it self
mainly relies on summary.glm(.).
---
As you see yourself, lrm() is from a particular CRAN package by
Prof Frank Harrell and if you really want that, you should ask
the package author -- as you are told in the posting guide
(you should read! -- see the last line of every R-help message).
Regards,
Martin Maechler <maechler at stat.math.ethz.ch> http://stat.ethz.ch/~maechler/
Seminar fuer Statistik, ETH-Zentrum LEO C16 Leonhardstr. 27
ETH (Federal Inst. Technology) 8092 Zurich SWITZERLAND
phone: x-41-1-632-3408 fax: ...-1228 <><
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