# [R] logististic regression (GLM). How to get 95 pct. confidence limits?

Prof Brian Ripley ripley at stats.ox.ac.uk
Sat Feb 28 09:17:22 CET 2004

```On Sat, 28 Feb 2004, Niels Steen Krogh wrote:

> Dear R-list.
> I'm doing af logistic analyses using gml.
> The model explaines variations in  Adverse events infections (0 og 1) using
> age as explanatory variable.
>
> model2d<-glm(formula=AEorSAEInfecBac~Age,family=binomial("logit"),data=emrisk)
>
> I want to get predictions with 95% confidence limits for age 30 and age 60.
> I've been reading the "google" and "search r-project" for suggestions but
> could only find solutions for lm: predict(model,data.frame(Age=30),level=.95
> ..............)
> ?predict.glm or ?glm did'nt give me hints either.

95% confidence limits for what?  I guess you mean either the linear
predictor or the mean, and it is preferable to find CIs for the linear
predictor and transforms the CIs if needed.

preds <- predict(model2d, data.frame(Age=c(30, 60)), se.fit=TRUE)

will give a list with means and ses for the linear predictor.  There is no
exact sampling theory, so you can use something like

cbind(lower=pred\$fit-1.96*preds\$se, upper=pred\$fit+1.96*preds\$se)

and transform by family(model2d)\$linkinv() to response scale.

--
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

```