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library(survival)
#
# Check that the survival curves from a Cox model with beta=0
# match ordinary survival
#
# Aalen
surv1 <- survfit(Surv(time,status) ~ sex, data=lung, stype=2)
fit1 <- coxph(Surv(time, status) ~ age + strata(sex), data=lung, iter=0,
ties='breslow')
fit1$var <- 0*fit1$var #sneaky, causes the extra term in the Cox variance
# calculation to be zero
surv2 <- survfit(fit1, stype=2)
surv3 <- survfit(fit1)
arglist <- c('n', 'time', 'n.risk','n.event', 'n.censor', 'surv', 'strata',
'std.err', 'upper', 'lower')
all.equal(unclass(surv1)[arglist], unclass(surv2)[arglist])
all.equal(unclass(surv1)[arglist], unclass(surv3)[arglist])
# Efron method
surv1 <- survfit(Surv(time,status) ~ sex, data=lung, stype=2, ctype=2)
surv2 <- survfit(fit1, ctype=2)
all.equal(unclass(surv1)[arglist], unclass(surv2)[arglist])
# Kaplan-Meier
surv1 <- survfit(Surv(time,status) ~ sex, data=lung)
surv2 <- survfit(fit1, stype=1)
all.equal(unclass(surv1)[arglist], unclass(surv2)[arglist])
# Now add some random weights
rwt <- runif(nrow(lung), .5, 3)
surv1 <- survfit(Surv(time,status) ~ sex, data=lung, stype=2, weights=rwt,
robust=FALSE)
fit1 <- coxph(Surv(time, status) ~ age + strata(sex), data=lung, iter=0,
ties='breslow', weights=rwt, robust=FALSE)
fit1$var <- 0*fit1$var #sneaky
surv2 <- survfit(fit1, stype=2, ctype=1)
surv3 <- survfit(fit1)
all.equal(unclass(surv1)[arglist], unclass(surv2)[arglist])
all.equal(unclass(surv1)[arglist], unclass(surv3)[arglist])
# Efron method
surv1 <- survfit(Surv(time,status) ~ sex, data=lung, stype=2, ctype=2,
weights=rwt, robust=FALSE)
surv2 <- survfit(fit1, ctype=2, robust=FALSE)
all.equal(unclass(surv1)[arglist], unclass(surv2)[arglist])
# Kaplan-Meier
surv1 <- survfit(Surv(time,status) ~ sex, data=lung, weights=rwt, robust=FALSE)
surv2 <- survfit(fit1, stype=1, robust=FALSE)
all.equal(unclass(surv1)[arglist], unclass(surv2)[arglist])
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