74 lines
2.5 KiB
R
74 lines
2.5 KiB
R
|
#
|
||
|
|
# Make sure that the newdata argument works for various
|
||
|
|
# predictions
|
||
|
|
# We purposely use a subset of the lung data that has only some
|
||
|
|
# of the levels of ph.ecog
|
||
|
|
library(survival)
|
||
|
|
options(na.action=na.exclude, contrasts=c('contr.treatment', 'contr.poly'))
|
||
|
|
aeq <- function(x,y) all.equal(as.vector(x), as.vector(y))
|
||
|
|
|
||
|
|
myfit <- coxph(Surv(time, status) ~ age + factor(ph.ecog) + strata(sex), lung)
|
||
|
|
|
||
|
|
keep <- which(lung$inst<13 & (lung$ph.ecog==1 | lung$ph.ecog==2))
|
||
|
|
p1 <- predict(myfit, type='lp')
|
||
|
|
p2 <- predict(myfit, type="lp", newdata=lung[keep,])
|
||
|
|
p3 <- predict(myfit, type='lp', se.fit=TRUE)
|
||
|
|
p4 <- predict(myfit, type="lp", newdata=lung[keep,], se.fit=TRUE)
|
||
|
|
aeq(p1[keep], p2)
|
||
|
|
aeq(p1, p3$fit)
|
||
|
|
aeq(p1[keep], p4$fit)
|
||
|
|
aeq(p3$se.fit[keep], p4$se.fit)
|
||
|
|
|
||
|
|
p1 <- predict(myfit, type='risk')
|
||
|
|
p2 <- predict(myfit, type="risk", newdata=lung[keep,])
|
||
|
|
p3 <- predict(myfit, type='risk', se.fit=TRUE)
|
||
|
|
p4 <- predict(myfit, type="risk", newdata=lung[keep,], se.fit=TRUE)
|
||
|
|
aeq(p1[keep], p2)
|
||
|
|
aeq(p1, p3$fit)
|
||
|
|
aeq(p1[keep], p4$fit)
|
||
|
|
aeq(p3$se.fit[keep], p4$se.fit)
|
||
|
|
|
||
|
|
# The all.equal fails for type=expected, Efron approx, and tied death
|
||
|
|
# times due to use of an approximation. See comments in the source code.
|
||
|
|
myfit <- coxph(Surv(time, status) ~ age + factor(ph.ecog) + strata(sex),
|
||
|
|
data=lung, method='breslow')
|
||
|
|
p1 <- predict(myfit, type='expected')
|
||
|
|
p2 <- predict(myfit, type="expected", newdata=lung[keep,])
|
||
|
|
p3 <- predict(myfit, type='expected', se.fit=TRUE)
|
||
|
|
p4 <- predict(myfit, type="expected", newdata=lung[keep,], se.fit=TRUE)
|
||
|
|
aeq(p1[keep], p2)
|
||
|
|
aeq(p1, p3$fit)
|
||
|
|
aeq(p1[keep], p4$fit)
|
||
|
|
aeq(p3$se.fit[keep], p4$se.fit)
|
||
|
|
|
||
|
|
p1 <- predict(myfit, type='terms')
|
||
|
|
p2 <- predict(myfit, type="terms",newdata=lung[keep,])
|
||
|
|
p3 <- predict(myfit, type='terms', se.fit=T)
|
||
|
|
p4 <- predict(myfit, type="terms",newdata=lung[keep,], se.fit=T)
|
||
|
|
aeq(p1[keep,], p2)
|
||
|
|
aeq(p1, p3$fit)
|
||
|
|
aeq(p1[keep,], p4$fit)
|
||
|
|
aeq(p3$se.fit[keep,], p4$se.fit)
|
||
|
|
|
||
|
|
#
|
||
|
|
# Check out the logic whereby predict does not need to
|
||
|
|
# recover the model frame. The first call should not
|
||
|
|
# need to do so, the second should in each case.
|
||
|
|
#
|
||
|
|
myfit <- coxph(Surv(time, status) ~ age + factor(sex), lung, x=T)
|
||
|
|
p1 <- predict(myfit, type='risk', se=T)
|
||
|
|
myfit2 <- coxph(Surv(time, status) ~ age + factor(sex), lung)
|
||
|
|
p2 <- predict(myfit2, type='risk', se=T)
|
||
|
|
aeq(p1$fit, p2$fit)
|
||
|
|
aeq(p1$se, p2$se)
|
||
|
|
|
||
|
|
p1 <- predict(myfit, type='expected', se=T)
|
||
|
|
p2 <- predict(myfit2, type='expected', se=T)
|
||
|
|
aeq(p1$fit, p2$fit)
|
||
|
|
aeq(p1$se.fit, p2$se.fit)
|
||
|
|
|
||
|
|
p1 <- predict(myfit, type='terms', se=T)
|
||
|
|
p2 <- predict(myfit2, type='terms', se=T)
|
||
|
|
aeq(p1$fit, p2$fit)
|
||
|
|
aeq(p1$se.fit, p2$se.fit)
|