larynx<-as.data.frame( scan("larynx.dat",
   what=list(stage=0,time=0,age=0,year=0,status=0)))
larynx$year<-larynx$year-74
stages23<-larynx[(larynx$stage==2)|(larynx$stage==3),]
library(survival)
cat('Larynx Cancer Survival Stages 2&3 Testing Stage\n')
survdiff(Surv(time,status)~factor(stage),data=stages23)
# Now fit proportional hazards model.  Use summary to
# give the score statistic as well.
cat('Larynx Cancer Survival Stages 2&3 Fitting Stage\n')
# Exact below corresponds to discrete in SAS
summary(coxph(Surv(time,status)~factor(stage),data=stages23,
   method="exact"))
cat('Larynx Cancer Survival Stages 2&3 Fitting Stage\n')
summary(coxph(Surv(time,status)~factor(stage),data=stages23,
   method="breslow"))
cat('Larynx Cancer Survival Stages 2&3 Fitting Stage\n')
# Efron is the default below.
summary(coxph(Surv(time,status)~factor(stage),data=stages23,
   method="efron"))
cat('Larynx Cancer Survival All Stages Fitting Stage\n')
coxph(Surv(time,status)~factor(stage),data=larynx)
cat('Larynx Cancer Survival All Stages Fitting Stage, Age\n')
coxph(Surv(time,status)~factor(stage)+age,data=larynx)
cat('Using stage as quant. instead of categorical\n')
coxph(Surv(time,status)~stage+age+year,data=larynx)
cat('An alternate parameterization of stage\n')
coxph(Surv(time,status)~factor(stage,levels=c(4,3,2,1))+age,
   data=larynx)
cat('Fitting all stages with age interaction\n')
coxph(Surv(time,status)~factor(stage)*age,data=larynx)