options(contrasts=c("contr.treatment", "contr.poly"))

acc.glm <- glm(nacc  ~ road + time + log(volume), data=accident, family=poisson)
summary(acc.glm)
anova(acc.glm, test="Chisq")


hod.glm <- glm(y~h+r, data=hodgkins, family=poisson)
summary(hod.glm)
anova(hod.glm, test="Chisq")

u <- resid(hod.glm, type="pearson") # The Pearson residuals are  saved in u
v <- resid(hod.glm, type="deviance") # The deviance residuals are saved in v
sum(u^2) # The result is the Pearson X^2 statistic
sum(v^2) # The result is the scaled deviance