The lrm function in the rms package will do this. David Schoeman wrote > Dear all. Apologies if I am asking a stupid question, but I have been > unable to find a solution so far. > > I would like to run a logistic regression in which individual data points > are assigned different weights (related to my confidence in their > validity). These individual observations are binary (success/failure). My > intuition was to use the "weights" option in the vlm function. Something > along the lines of: > mod1 <- glm(success ~ beach - 1, weights = confidence, data = dat, > family > = binomial), > where success is binary (1/0), beach is a factor and weights are either 1 > (full confidence) or 0.5 (less confidence). > > When I ran into the "non-integer #successes in a binomial vlm!" error, and > read the help files, I realised my error (in binomial glm, weights set the > number of trials). It's good to know WHY my approach was wrong, but it > would be better to know how to conduct my analysis correctly. > > Any ideas appreciated. > > Dave > ______________________________________________
> R-help@ > 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. ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Is-there-any-way-of-weighting-individual-data-points-in-a-logistic-regression-tp4647508p4647545.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
