On Sep 11, 2010, at 3:15 PM, Maik Rehnus wrote:
Dear all,
I have a quasipoisson glm for which I need confidence bands in a
graphic:
gm6 <- glm(num_leaves ~ b_dist_min_new, family = quasipoisson, data
= beva)
summary(gm6)
library('VIM')
b_dist_min_new <- as.numeric(prepare(beva$dist_min,
scaling="classical", transformation="logarithm")).
My first steps for the solution are following:
range(b_dist_min_new)
x <- seq(-1.496, 1.839, by=0.01)
newdat <- data.frame(b_dist_min_new=x)
y <- predict(gm6, newdata=newdat, type="response")
plot(x,y, type="l", ylim=c(0,15), lty=2, xlab="Distance [scaled
log.]", ylab="Number of used plant", las=1)
ilogit<-function(x) exp(x)/(1 + exp(x))
logit <-function(x) log(x/(1 - x))
newdat$logitpred <- predict(gm6, newdata=newdat, type="link")
I'm puzzled. You specified that model as quasipoisson and are now
treating it as if it were logistic? The link is going to be log(),
nicht wahr?
newdat$sepred <- predict(gm6, newdata=newdat, type="link",
se.fit=TRUE)$se.fit
newdat$logitlower <- newdat$logitpred-1.96 * newdat$sepred
newdat$logitupper <- newdat$logitpred+1.96 * newdat$sepred
I'm not familiar with ilogit (sounds very useful assuming it to be an
inverse logit), but if one were taking a first stab at an inverse
function for quasipoisson wouldn't that be exp()?
newdat$upper <- ilogit(newdat$logitupper)
newdat$lower <- ilogit(newdat$logitlower)
lines(x, newdat$lower, lty=3)
lines(x, newdat$upper, lty=3).
In this way I could find a positive correlation. But my created
confidence bands on the graph don't touch my regression line. Could
it be a technical problem or is it a mistake in the calculation?
I am new here and I hope you can help to solve my problem. I could
not find any answers for quasipoisson glm on internet.
Best regards
Maik
David Winsemius, MD
West Hartford, CT
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