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-twigs@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
>
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>
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