[R] Poisson GLM

[David Winsemius]

Since one method of modeling rates is to use  
glm(...  ,family="poisson") with the observed rate (events/ 
person_time) on the LHS of the formula and offset=log(expected_rates)  
on the RHS, I am quite happy that no error is thrown in that situation.

Reading old entries in r-help, it appears there may have been a time  
when an error was thrown, but now you just get a warning (assuming  
that people were not misreporting what they were seeing). Quasi- 
poisson models were recommended as an alternative.

?family

using a distorted version of the family = poisson() example in glm()  
help page:
 > d.AD[1,3] <- 17.5

 > glm.D93 <- glm(counts ~ outcome + treatment, data=d.AD,  
family=poisson())
Warning message:
In dpois(y, mu, log = TRUE) : non-integer x = 17.500000

 > glm.qD93 <- glm(counts ~ outcome + treatment, data= d.AD,  
family=quasipoisson())
#no warning

 > coef(glm.qD93)
(Intercept)    outcome2    outcome3  treatment2  treatment3
  3.02984283 -0.44628710 -0.28501896  0.01005034  0.01005034
 >
 > coef(glm.D93)
(Intercept)    outcome2    outcome3  treatment2  treatment3
  3.02984283 -0.44628710 -0.28501896  0.01005034  0.01005034

# although vcov shows a difference
-- 
David Winsemius





On Jan 20, 2009, at 12:14 PM, bbbnc wrote:

>
> This is a basics beginner question.
>
> I attempted fitting a a Poisson GLM to data that is non-integer ( I  
> believe
> Poisson is suitable in this case, because it is modelling counts of
> infections, but the data collected are all non-negative numbers with 2
> decimal places).
>
> My question is, since R doesn't return an error with this glm  
> fitting, is it
> important that the data is non-integer. How does R handle the data?  
> if there
> is a problem, how do i circumvent this.. data modification?
>
> many thanks
> -- 
> View this message in context: http://www.nabble.com/Poisson-GLM-tp21567460p21567460.html
> Sent from the R help mailing list archive at Nabble.com.
>
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