# Survival curve for the "average" subject
summary(survfit(sfit.1))

# Survival curve for a subject of age 50, with prior surgery, tx at 6 months
data <- data.frame(start=c(0,183), stop=c(183,3*365), event=c(1,1),
		   age=c(50,50),  surgery=c(1,1), transplant=c(0,1))
summary(survfit(sfit.1, data, individual=T))

# These should all give the same answer
j.age <- jasa$age/365.25 -48
fit1 <- coxph(Surv(futime, fustat) ~ j.age, data=jasa)
fit2 <- coxph(Surv(futime, fustat) ~ j.age, jasa, init=fit1$coef, iter=0)
fit3 <- coxph(Surv(start, stop, event) ~ age)
fit4 <- coxph(Surv(start, stop, event) ~ offset((age-fit3$means)*fit1$coef))
s1 <- survfit(fit1, fit3$means)
s2 <- survfit(fit2, fit3$means)
s3 <- survfit(fit3)
s4 <- survfit(fit4)

all.equal(s1$surv, s2$surv)
all.equal(s1$surv, s3$surv)
all.equal(s1$surv, s4$surv)

# Still the same answer, fit multiple strata at once
#  Strata 1 has independent coefs of strata 2, so putting in
#    the other data should not affect it
ll <- length(start)
ss <- rep(0:1, c(ll,ll))
fit <- coxph(Surv(rep(start,2), rep(stop,2), rep(event,2)) ~
			rep(age,2)*strata(ss) + I(rep(age,2)^2*ss) )
fit$coef[1] - fit3$coef
s4 <- survfit(fit, c(fit3$means, 0,0))
all.equal(s4$surv[1:(s4$strata[1])],  s3$surv)
detach("jasa1")