[R] confidence interval for glm

[Gavin Simpson]

On Sun, 2008-11-30 at 01:15 -0500, David Winsemius wrote:
> ?confint.glm   # ... in MASS

That provides confidence intervals on the parameters of the model, which
is not what the OP wanted. He wants confidence intervals on:

predict(mod, newdat)

One way to do this is to compute them in the normal way but do so on the
scale of the link function. Then transform those confidence intervals on
to the scale of the response by applying the inverse of the link
function used in the GLM. One way to do this is the following: [not
tested as no reproducible code to try it on]

## compute the predicted values on the scale of the link
preds <- predict(mod, newdata = pred.data, se.fit = TRUE)

## where mod and pred.data are your glm model and 
## points at which you wish to evaluate the fitted function.
## leave out newdata = pred.data if you want the fitted values

## get inverse of link as a function
ilogit <- family(mod)$linkinv

## compute standard confidence intervals (2 * se.fit)
ci.u <- with(preds, fit + (2 * se.fit))
ci.l <- with(preds, fit - (2 * se.fit))
## change 2 to be a quantile from the t distribution for your level
## of confidence (2 is approximately 95% for large n)
##
## something like for 95%, N is sample size;
## (hope I got the correction for df right here, no doubt someone will
## correct me if wrong), and use crit.t in place of 2 above.
crit.t <- qt(0.975, df = N-1)

## compute predictions on scale of response by applying ilogit
preds <- ilogit(preds$fit)

## transform conf int on to scale of response
ci.u <- ilogit(ci.u)
ci.l <- ilogit(ci.l)

Is that what you were looking for?

G

> 
> On Nov 28, 2008, at 9:29 AM, Gerard M. Keogh wrote:
> 
> >
> > Hi all,
> >
> > simple Q:
> >
> > how do I extract the upper and lower CI for predicted probabilities
> > directly for a glm - I'm sure there's a one line to do it but I  
> > can't find
> > it.
> > the predicted values I get with the predict (.. "response")
> >
> > Thanks
> >
> > Gerard
> >
> >
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