Hi: Using package sos:
# install.packages('sos') # if necessary library(sos) findFn('conditional logistic regression') the following appear to be reasonable candidates to start investigating: * clogit() in package survival * clogistic() in package Epi * clogistCalc() in package saws * the TwoStepClogit package HTH, Dennis On Sat, Feb 26, 2011 at 10:37 PM, array chip <arrayprof...@yahoo.com> wrote: > Hi, I am wondering if there is a package for doing conditional logistic > regression for nested case-control study as described in "Estimation of > absolute > risk from nested case-control data" by Langholz and Borgan (1997) where > Horvitz-Thompson sampling weight (log of (number in the risk set divided by > the > number sampled)) is used with regression. In SAS Proc Phreg, this is > implemented > as an offset (offset=logweight). I checked clogistic() in Epi package and > clogit() in survival package, but couldn't figure out how to incorporate > this > weighting with either. > > > Also when considering nested case-control sampling for Cox proportional > hazards > model, the above method can estimate absolute risk of developing disease > over a > specified time interval. Appreciate if anyone has any suggestion on how to > do > this in R. > > Thanks very much! > > John > > > > [[alternative HTML version deleted]] > > > ______________________________________________ > 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. > > [[alternative HTML version deleted]] ______________________________________________ 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.