alc<- factor(rep(c("y","n"),c(8,8)))
cig<- factor(rep(c("y","n","y","n"),c(4,4,4,4)))
gender<-factor(rep(rep(c("f","m"),4),rep(2,8)))
mj<- factor(rep(c("y","n"),8))
counts<-c(428,291,483,247,15,237,29,219,1,18,2,25,1,129,1,140)
nacm.fit1<-glm(counts~alc+cig+gender+mj,family=poisson)
nacm.steps<-step(nlc<- factor(rep(c("y","n"),c(8,8)))
cig<- factor(rep(c("y","n","y","n"),c(4,4,4,4)))
gender<-factor(rep(rep(c("f","m"),4),rep(2,8)))
mj<- factor(rep(c("y","n"),8))
counts<-c(428,291,483,247,15,237,29,219,1,18,2,25,1,129,1,140)
nacm.fit1<-glm(counts~alc+cig+gender+mj,family=poisson)
nacm.steps<-step(nacm.fit1,scope=list(lower=~alc+cig+gender+mj,upper=~(alc+cig+gender+mj)^3))
acm.fit1,scope=list(lower=~alc+cig+gender+mj,upper=~(alc+cig+gender+mj)^3))