library(survival)
source("http://myweb.uiowa.edu/pbreheny/7210/f18/notes/fun.R")


# Origin-time models ------------------------------------------------------

# Unconditional
fit <- coxph(Surv(start, stop, event) ~ rx + number + size, bladder2)
summary(fit)

# As covariate
fit <- coxph(Surv(start, stop, event) ~ rx + number + size + factor(enum), bladder2)
summary(fit)

# Stratifying
fit <- coxph(Surv(start, stop, event)~ rx + number + size + strata(enum), bladder2)
summary(fit)
plot(survfit(fit), mark.time=FALSE, col=pal(4), lwd=3, bty='n', las=1,
     xlab='Time (Months)', ylab='Baseline survival')
toplegend(legend=1:4, col=pal(4), lwd=3)
summary(fit1 <- coxph(Surv(start, stop, event)~ rx + number + size, bladder2, subset=(enum==1)))
summary(fit2 <- coxph(Surv(start, stop, event)~ rx + number + size, bladder2, subset=(enum==2)))
summary(fit3 <- coxph(Surv(start, stop, event)~ rx + number + size, bladder2, subset=(enum==3)))
summary(fit4 <- coxph(Surv(start, stop, event)~ rx + number + size, bladder2, subset=(enum==4)))


# Gap-time models ---------------------------------------------------------

bladder2$gaptime <- with(bladder2, stop - start)

# Unconditional
fit <- coxph(Surv(gaptime, event)~ rx + number + size, bladder2)
summary(fit)

# As covariate
fit <- coxph(Surv(gaptime, event)~ rx + number + size + factor(enum), bladder2)
summary(fit)

# Stratify
fit <- coxph(Surv(gaptime, event)~ rx + number + size + strata(enum), bladder2)
summary(fit)
plot(survfit(fit), mark.time=FALSE, col=pal(4), lwd=3, bty='n', las=1,
     xlab='Time (Months)', ylab='Baseline survival')
toplegend(legend=1:4, col=pal(4), lwd=3)
summary(fit1 <- coxph(Surv(gaptime, event)~ rx + number + size, bladder2, subset=(enum==1)))
summary(fit2 <- coxph(Surv(gaptime, event)~ rx + number + size, bladder2, subset=(enum==2)))
summary(fit3 <- coxph(Surv(gaptime, event)~ rx + number + size, bladder2, subset=(enum==3)))
summary(fit4 <- coxph(Surv(gaptime, event)~ rx + number + size, bladder2, subset=(enum==4)))