R help - Feb 2004 - logististic regression (GLM). How to get 95 pct. confidence limits?

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.


Using R1.8.1. Windows





Cand. Polit.
Niels Steen Krogh
Solsortvej 44
2000 F.

Tlf: 3888 8613

ZiteLab / EmpoweR youR data with R, Zope and SOAP

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

Hi,

in library(MASS) the function  profile.glm  should help you.

christian



Am Samstag, 28. Februar 2004 08:22 schrieb Niels Steen
Krogh:
> 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=emri
>sk)
>
> 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.
>
>
> Using R1.8.1. Windows
>
>
>
>
>
> Cand. Polit.
> Niels Steen Krogh
> Solsortvej 44
> 2000 F.
>
> Tlf: 3888 8613
>
> ZiteLab / EmpoweR youR data with R, Zope and SOAP
>
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