R Under development (unstable) (2024-12-13 r87441 ucrt) -- "Unsuffered Consequences"
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> #
> # 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$ph.ecog==2))
> p1 <- predict(myfit, type='lp')
> p2 <- predict(myfit, type="lp", newdata=lung[keep,])
> p3 <- predict(myfit, type='lp', se.fit=TRUE)
> p4 <- predict(myfit, type="lp", newdata=lung[keep,], se.fit=TRUE)
> aeq(p1[keep], p2)
[1] TRUE
> aeq(p1, p3$fit)
[1] TRUE
> aeq(p1[keep], p4$fit)
[1] TRUE
> aeq(p3$se.fit[keep], p4$se.fit)
[1] TRUE
> 
> p1 <- predict(myfit, type='risk')
> p2 <- predict(myfit, type="risk", newdata=lung[keep,])
> p3 <- predict(myfit, type='risk', se.fit=TRUE)
> p4 <- predict(myfit, type="risk", newdata=lung[keep,], se.fit=TRUE)
> aeq(p1[keep], p2)
[1] TRUE
> aeq(p1, p3$fit)
[1] TRUE
> aeq(p1[keep], p4$fit)
[1] TRUE
> aeq(p3$se.fit[keep], p4$se.fit)
[1] TRUE
> 
> # The all.equal fails for type=expected, Efron approx, and tied death
> #  times due to use of an approximation.  See comments in the source code.
> myfit <- coxph(Surv(time, status) ~ age + factor(ph.ecog) + strata(sex), 
+                data=lung, method='breslow')
> p1 <- predict(myfit, type='expected')
> p2 <- predict(myfit, type="expected", newdata=lung[keep,])
> p3 <- predict(myfit, type='expected', se.fit=TRUE)
> p4 <- predict(myfit, type="expected", newdata=lung[keep,], se.fit=TRUE)
> aeq(p1[keep], p2)
[1] TRUE
> aeq(p1, p3$fit)
[1] TRUE
> aeq(p1[keep], p4$fit)
[1] TRUE
> aeq(p3$se.fit[keep], p4$se.fit)
[1] TRUE
> 
> p1 <- predict(myfit, type='terms')
> p2 <- predict(myfit, type="terms",newdata=lung[keep,])
> p3 <- predict(myfit, type='terms', se.fit=T)
> p4 <- predict(myfit, type="terms",newdata=lung[keep,], se.fit=T)
> aeq(p1[keep,], p2)
[1] TRUE
> aeq(p1, p3$fit)
[1] TRUE
> aeq(p1[keep,], p4$fit)
[1] TRUE
> aeq(p3$se.fit[keep,], p4$se.fit)
[1] TRUE
> 
> #
> # Check out the logic whereby predict does not need to
> #  recover the model frame.  The first call should not 
> #  need to do so, the second should in each case.
> #
> myfit <- coxph(Surv(time, status) ~ age + factor(sex), lung, x=T)
> p1 <- predict(myfit, type='risk', se=T)
> myfit2 <- coxph(Surv(time, status) ~ age + factor(sex), lung)
> p2 <- predict(myfit2, type='risk', se=T)
> aeq(p1$fit, p2$fit)
[1] TRUE
> aeq(p1$se, p2$se)
[1] TRUE
> 
> p1 <- predict(myfit, type='expected', se=T)
> p2 <- predict(myfit2, type='expected', se=T)
> aeq(p1$fit, p2$fit)
[1] TRUE
> aeq(p1$se.fit, p2$se.fit)
[1] TRUE
> 
> p1 <- predict(myfit, type='terms', se=T)
> p2 <- predict(myfit2, type='terms', se=T)
> aeq(p1$fit, p2$fit)
[1] TRUE
> aeq(p1$se.fit, p2$se.fit)
[1] TRUE
> 
> proc.time()
   user  system elapsed 
   1.28    0.09    1.35