mutant.fit<-glm(count~mutation+cancer,family=poisson(link=log),
            data=mutant.p53.df)
 mutant.pearson.x2<- sum(resid(mutant.fit,type="pearson")^2)

 mutant.expected<-predict(mutant.fit,type="response")

 zd(mutant.pearson.x2,mutant.tab,mutant.p53.df$count,mutant.expected)


           D        mu    sigma        Z            p
1 18.57962 -6.859649 3.702812 6.870256 6.408651e-12