#**********************************************************
# Data excerpted from NIH Multi Center AIDS Cohort Study. *
# Cohort consists of gay and bisexual men.  Variables are *
# happy: self-reported level of happiness at enrollment   *
# time: time to death or loss to followup,                *
# entry: age at first follow-up, status: 1 for death, 0 ow*
# life: finer self-reported happiness measure             *
# aaids: age at development of aids.                      *
#**********************************************************
library(survival)
mcac<-as.data.frame(scan("mcac.dat",
   what=list(helth=0,life=0,happy=0,status=0,entry=0,time=0,aaids=0)))
mcac<-mcac[mcac$helth>0,]
mcac$aids<-FALSE
mcac$neveraids<-mcac$aaids>=mcac$time
mcac$person<-seq(length(mcac$time))
tempdat<-mcac; tempdat$aids<-TRUE
bigmcac<-rbind(mcac,tempdat)
bigmcac<-bigmcac[!(bigmcac$neveraids&bigmcac$aids),]
bigmcac$entry[bigmcac$aids]<-bigmcac$aaids[bigmcac$aids]
bigmcac$time[!bigmcac$aids]<-bigmcac$aaids[!bigmcac$aids]
bigmcac<-bigmcac[bigmcac$entry<bigmcac$time,]
bigmcac$status<-bigmcac$status*(bigmcac$neveraids|bigmcac$aids)
bigmcac$aids<-1*bigmcac$aids
bigmcac<-bigmcac[order(bigmcac$person),]
source("l09f.R")
postscript("l09.ps")
par(mfrow=c(2,2))
fun.csplot(bigmcac,"time","entry","status","Ignoring AIDS status",
   trycov1="helth")
fun.csplot(bigmcac,"time","entry","status","Stratifying on AIDS status",
   strat="aids",trycov1="helth")
fun.csplot(bigmcac,"time","entry","status",
   "Stratifying on AIDS status, Adjusting for Health",
   covs="helth", strat="aids",trycov1="helth",plotscore=1)