On Dec 12, 2009, at 8:19 PM, casperyc wrote:
for an example,
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9); treatment <- gl(3,3)
glm.D93 <- glm(counts ~ outcome + treatment, family=poisson())
confint(glm.D93)
confint.default(glm.D93) # based on asymptotic normality
to verify the confidence interval (confint.default(glm.D93)) for
outcome2
-4.542553e-01 + c(-1,1) * 0.2021708 * qt(0.975,df=4)
-1.0155714 0.1070608
does not give me
outcome2 -0.8505027 -0.05800787
as in confint.default(glm.D93)
But this does (up to rounding anyway):
> coef(summary(glm.D93))[2,1] + c(-1,1) * coef(summary(glm.D93))
[2,2]*qnorm(0.975)
[1] -0.85050267 -0.05800787
I can understand thinking that the CI's might be t-distributed but the
usual formulation is that they are normally distributed.
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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