R Under development (unstable) (2024-12-13 r87441 ucrt) -- "Unsuffered Consequences"
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> #
> # Formal test of the quantile routine for survfit
> library(survival)
> aeq <- function(x, y, ...) all.equal(as.vector(x), as.vector(y), ...)
> 
> # There are 8 cases:  strata Y/N,  ncol(surv) >1,  conf.int = T/F
> #  Subcase: the quantile exactly agrees with a horizontal segment of 
> #    the curve or not.
> # First do the 4 cases where fit$surv is a vector
> #
> test1 <- data.frame(time=  c(9, 3,1,1,6,6,8, 10),
+                     status=c(1,NA,1,0,1,1,0,  0),
+                     x=     c(0, 2,1,1,1,0,0,  0))
> 
> # True survival = (6/7) * (3/5) * (1/2) for overall
> #   The q's are chosen to include a point < first jump, mid, after last jump,
> #   and exact intersections with the "flats" of the curve.
> #   
> qq <- c(13/14, 6/7, 2/3, .5, 9/35, .1)
>  
> # Nothing on the right hand side, simple survival (no strata)
> fit1 <- survfit(Surv(time, status) ~ 1, test1, conf.type='none')
> aeq(quantile(fit1, 1-qq), c(1, 3.5, 6, 9, 9.5, NA))  #without conf.int
[1] TRUE
> 
> fit2 <-  survfit(Surv(time, status) ~ 1, test1)  #with conf.int
> aeq(quantile(fit2, 1-qq), 
+     list(quantile = c(1, 3.5, 6, 9, 9.5, NA),
+          lower = c(1,1,1,6,6,9),
+          upper = rep(as.numeric(NA), 6)), check.attributes=FALSE)
[1] TRUE
> aeq(quantile(fit2, 1-qq, FALSE), c(1, 3.5, 6, 9, 9.5, NA)) 
[1] TRUE
> 
> 
> # Now a variable on the right (strata in the result)
> #  curve 0: (t=6, S=3/4),  (t=9, S=3/8)
> #  curve 1: (t=1, S=2/3),  (t=6, S= 0)
> fit1 <- survfit(Surv(time, status) ~ x, test1, conf.type='none') 
> aeq(quantile(fit1, 1-qq),
+     matrix(c(6,6,9,9,NA,NA,  1,1,3.5, 6,6,6), nrow=2, byrow=T))
[1] TRUE
> 
> fit2 <- survfit(Surv(time, status) ~ x, test1)
> aeq(quantile(fit2, 1-qq, FALSE),
+     matrix(c(6,6,9,9,NA,NA,  1,1,3.5, 6,6,6), nrow=2, byrow=T))
[1] TRUE
> 
> temp <- quantile(fit2, 1-qq)
> aeq(temp$quantile, matrix(c(6,6,9,9,NA,NA,  1,1,3.5, 6,6,6), nrow=2, byrow=T))
[1] TRUE
> aeq(temp$lower,    matrix(c(6,6,6,6,9,9,    1,1,1,1, NA,NA), nrow=2, byrow=T))
[1] TRUE
> aeq(temp$upper,    rep(as.numeric(NA), 12))
[1] TRUE
> 
> # Second major case set -- a survfit object where fit$surv is a matrix
> #  This arises from coxph models
> #  There is only 1 subject with ph.ecog=3 which is a nice edge case
> cfit <- coxph(Surv(time, status) ~ age + strata(ph.ecog), lung)
> sfit <- survfit(cfit, newdata=data.frame(age=c(50, 70)))
> qtot <- quantile(sfit, qq)
> for (i in 1:4) {
+     for (j in 1:2) {
+         temp <- quantile(sfit[i,j], qq)
+         print(c(aeq(qtot$quantile[i,j,], temp$quantile),
+                 aeq(qtot$upper[i,j,], temp$upper),
+                 aeq(qtot$lower[i,j,], temp$lower)))
+     }
+ }
[1] TRUE TRUE TRUE
[1] TRUE TRUE TRUE
[1] TRUE TRUE TRUE
[1] TRUE TRUE TRUE
[1] TRUE TRUE TRUE
[1] TRUE TRUE TRUE
[1] TRUE TRUE TRUE
[1] TRUE TRUE TRUE
> temp <- quantile(sfit, qq, conf.int=FALSE)
> all.equal(qtot$quantile, temp)
[1] TRUE
> 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
   0.79    0.14    0.92