a closer look to the help on predict.glm will reveal that the function accepts a 'type' argument. In you case 'type = response' will give you the results in probabilities (that it seems to be what you are looking for). There also is an example on use of the 'type' argument at the end of the page.
Stefano -----Messaggio originale----- Da: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]per conto di Troy S Inviato: Friday, August 06, 2010 6:31 PM A: Michael Bedward Cc: r-help@r-project.org Oggetto: Re: [R] Confidence Intervals for logistic regression Michael, Thanks for the reply. I believe Aline was sgiving me CI's on coefficients as well. So c(pred$fit + 1.96 * pred$se.fit, pred$fit - 1.96 * pred$se.fit) gives me the CI on the logits if I understand correctly? Maybe the help on predict.glm can be updated. Thanks! On 6 August 2010 01:46, Michael Bedward <michael.bedw...@gmail.com> wrote: > 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. > > > [[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. Rispetta l'ambiente: Se non ti è necessario, non stampare questa mail. "Le informazioni contenute nel presente messaggio di posta elettronica e in ogni suo allegato sono da considerarsi riservate e il destinatario della email è l'unico autorizzato ad usarle, copiarle e, sotto la propria responsabilità, divulgarle. Chiunque riceva questo messaggio per errore senza esserne il destinatario deve immediatamente rinviarlo al mittente cancellando l'originale. Eventuali dati personali e sensibili contenuti nel presente messaggio e/o suoi allegati vanno trattati nel rispetto della normativa in materia di privacy ( DLGS n.196/'03)". ______________________________________________ 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.
