Sorry about earlier reply - didn't read your email properly (obviously :) You're suggestion was right, so as well as method for Aline below, another way of doing the same thing is:
pred <- predict(y.glm, newdata= something, se.fit=TRUE) ci <- matrix( c(pred$fit + 1.96 * pred$se.fit, pred$fit - 1.96 * pred$se.fit), ncol=2 ) lines( something, plogis( ci[,1] ) ) lines( something, plogis( ci[,2] ) ) On 6 August 2010 18:39, aline uwimana <rwan...@gmail.com> wrote: > Dear Troy, > use this commend, your will get IC95% and OR. > > logistic.model <- glm(formula =y~ x1+x2, family = binomial) > summary(logistic.model) > > sum.coef<-summary(logistic.model)$coef > > est<-exp(sum.coef[,1]) > upper.ci<-exp(sum.coef[,1]+1.96*sum.coef[,2]) > lower.ci<-exp(sum.coef[,1]-1.96*sum.coef[,2]) > > cbind(est,upper.ci,lower.ci) > > regards. > > 2010/8/6 Troy S <troysocks-tw...@yahoo.com> > >> Dear UseRs, >> >> I have fitted a logistic regression using glm and want a 95% confidence >> interval on a response probability. Can I use >> >> predict(model, newdata, se.fit=T) >> >> Will fit +/- 1.96se give me a 95% of the logit? And then >> exp(fit +/- 1.96se) / (exp(fit +/- 1.96se) +1) to get the probabilities? >> >> Troy >> >> [[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. > ______________________________________________ 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.
