chd.data <- importData("c:\\OldE\\M3S12\\Data\\CHD.xls")

#Number of data points
n<-nrow(chd.data) 

chd.y<-chd.data$CHD
chd.x<-chd.data$AGRP
chd.x[chd.data$AGRP <= 6]<-0 #NON EXPOSED, <= 55
chd.x[chd.data$AGRP > 6]<-1  #EXPOSED > 55


chd.data55<-data.frame(chd.x,chd.y)
names(chd.data55)<-c("OVER.55","CHD")

#OVER.55 = 1 if over 55, OVER.55 = 0 otherwise

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

#Fit the "null" GLM, where the linear predictor is constant
fit.0_glm(CHD ~ 1,family=binomial,data=chd.data55)
summary(fit.0)

#Fit the model with OVER.55 as the only predictor
fit.1_glm(CHD ~ factor(OVER.55),family=binomial,data=chd.data55)
summary(fit.1)