Stefano, I was aware of this option. I was assuming it was not ok to do fit +/- 1.96 se when you requested probabilities. If this is legitimate then all the better.
Thanks! Troy On 6 August 2010 22:25, Guazzetti Stefano <stefano.guazze...@ausl.re.it>wrote: > 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)". > > [[alternative HTML version deleted]]
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