Dear members,
here is my trouble: My data consists of counts of trapped insects in different
attractive traps. I usually use GLMs with a poisson error distribution to find
out the differences between my traitments (and to look at other factor
effects). But for some dataset where one traitment contains only zeros, GLM
with poisson family fail to find any difference between this particular
traitment and anyother one (even with traitment that have trapped a lot of
insects). GLMs with gaussian family does not seem to have the same problem but
GLMs with binomial family does.
I'm not sure if it is a statistical problem or if it comes from R... in the
latter case I think some solution exists (perhaps in the options of the glm()
function ?).
Thank you for your help.
Here I figure out an exemple to past in the console:
## START
##############################################################################
# Take a data set of counts for two traitments, one containing only zeros
A=c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
B=c(1,0,0,0,2,1,0,0,1,2,0,0,0,1,2,2,0,1,1,0,1,0,2,1,1,0,1,2,0,1,0,1,1,1,0,1,1,1,0,1)
traitment=c(rep("A",40),rep("B",40))
response=c(A,B)
mydata=data.frame(traitment ,response)
# Make a GLM on this dataset , with "family=poisson"
g=glm(response~traitment, data=mydata, family=poisson)
anova.glm(g,test="Chisq")
# There is an effect of the traitment ...
summary(g)
# But traitment A does not differ from traitment B ! ! ! (the pvalue is always
close from 1 in such cases)
# Now if you replace only one zero of the A reponse to 1, the GLM works
properly:
mydata[1,2]=1
g=glm(response~traitment, data=mydata, family=poisson)
anova.glm(g,test="Chisq")
summary(g)
#####################################################################################
END ##
Antonin Ferry (PhD)
"Laboratoire d'Ecobiologie des Insectes Parasitoides"
http://www.parasitoides.univ-rennes1.fr
Université de Renes1, FRANCE
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