Since you have provided no executable data and not even a clear enough
description of the data to offer advice regarding approaches or
pitfalls, I will use the example in glm's help page:
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
glm.D93r <- glm(counts ~ outcome, family=poisson())
plot(x=as.numeric(as.character(outcome)), y=counts, type="p") #need
to convert from factor to ge points
lines(1:3, c(exp(3.045), exp(3.0445 -0.4543), exp(3.0445 -0.2930) ) )
#the default link for poisson is log, so you need to transform back to
the original scale to predict counts.
On Jun 7, 2009, at 11:36 PM, Jo Stringer wrote:
I have fitted two glms assuming a poisson distribution which are:
fit1 <- glm(Aids ~ Year, data=aids, family=poisson())
fit2 <- glm(Aids ~ Year+I(Year^2), data=aids, family=poisson())
I am trying to work out how to represent the fitted regression
curves of fit1 and fit2 on the one graph. I have tried:
graphics.off()
plot(Aids ~ Year, data = aids)
line(glm(Aids ~ Year, data=aids, family=poisson()))
line(glm(Aids ~ Year+I(Year^2), data=aids, family=poisson()))
but this does not work.
Can anyone help me?
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
