# tests/book4.R In survival: Survival Analysis

```options(na.action=na.exclude) # preserve missings
options(contrasts=c('contr.treatment', 'contr.poly')) #ensure constrast type
library(survival)

#
# Tests from the appendix of Therneau and Grambsch
#  d. Data set 2 and Efron estimate
#
test2 <- data.frame(start=c(1, 2, 5, 2, 1, 7, 3, 4, 8, 8),
stop =c(2, 3, 6, 7, 8, 9, 9, 9,14,17),
event=c(1, 1, 1, 1, 1, 1, 1, 0, 0, 0),
x    =c(1, 0, 0, 1, 0, 1, 1, 1, 0, 0))

byhand <- function(beta, newx=0) {
r <- exp(beta)
loglik <- 4*beta - (log(r+1) + log(r+2) + 2*log(3*r+2) + 2*log(3*r+1) +
log(2*r +2))
u <- 1/(r+1) +  1/(3*r+1) + 2*(1/(3*r+2) + 1/(2*r+2)) -
( r/(r+2) +3*r/(3*r+2) + 3*r/(3*r+1))
imat <- r*(1/(r+1)^2 + 2/(r+2)^2 + 6/(3*r+2)^2 +
6/(3*r+1)^2 + 6/(3*r+2)^2 + 4/(2*r +2)^2)

hazard <-c( 1/(r+1), 1/(r+2), 1/(3*r+2), 1/(3*r+1), 1/(3*r+1),
1/(3*r+2), 1/(2*r +2) )

# The matrix of weights, one row per obs, one col per time
#   deaths at 2,3,6,7,8,9
wtmat <- matrix(c(1,0,0,0,1, 0, 0,0,0,0,
0,1,0,1,1, 0, 0,0,0,0,
0,0,1,1,1, 0, 1,1,0,0,
0,0,0,1,1, 0, 1,1,0,0,
0,0,0,0,1, 1, 1,1,0,0,
0,0,0,0,0, 1, 1,1,1,1,
0,0,0,0,0,.5,.5,1,1,1), ncol=7)
wtmat <- diag(c(r,1,1,r,1,r,r,r,1,1)) %*% wtmat

x      <- c(1,0,0,1,0,1,1,1,0,0)
status <- c(1,1,1,1,1,1,1,0,0,0)
xbar <- colSums(wtmat*x)/ colSums(wtmat)
n <- length(x)

# Table of sums for score and Schoenfeld resids
hazmat <- wtmat %*% diag(hazard) #each subject's hazard over time
dM <- -hazmat  #Expected part
for (i in 1:5) dM[i,i] <- dM[i,i] +1  #observed
dM[6:7,6:7] <- dM[6:7,6:7] +.5  # observed
mart <- rowSums(dM)

# Table of sums for score and Schoenfeld resids
#  Looks like the last table of appendix E.2.1 of the book
resid <- dM * outer(x, xbar, '-')
score <- rowSums(resid)
scho <- colSums(resid)

# We need to add the ties back up (they are symmetric)
scho[6:7] <- rep(mean(scho[6:7]), 2)

list(loglik=loglik, u=u, imat=imat, xbar=xbar, haz=hazard,
mart=mart,  score=score, rmat=resid,
scho=scho)
}

aeq <- function(x,y) all.equal(as.vector(x), as.vector(y))

fit0 <-coxph(Surv(start, stop, event) ~x, test2, iter=0)
truth0 <- byhand(0,0)
aeq(truth0\$loglik, fit0\$loglik[1])
aeq(1/truth0\$imat, fit0\$var)
aeq(truth0\$mart, fit0\$resid)
aeq(truth0\$scho, resid(fit0, 'schoen'))
aeq(truth0\$score, resid(fit0, 'score'))

fit <- coxph(Surv(start, stop, event) ~x, test2, eps=1e-8, nocenter=NULL)
truth <- byhand(fit\$coef, 0)
aeq(truth\$loglik, fit\$loglik[2])
aeq(1/truth\$imat, fit\$var)
aeq(truth\$mart, fit\$resid)
aeq(truth\$scho, resid(fit, 'schoen'))
aeq(truth\$score, resid(fit, 'score'))

# Reprise the test, with strata
#  offseting the times ensures that we will get the wrong risk sets
#  if strata were not kept separate
test2b <- rbind(test2, test2, test2)
test2b\$group <- rep(1:3, each= nrow(test2))
test2b\$start <- test2b\$start + test2b\$group
test2b\$stop  <- test2b\$stop  + test2b\$group
fit0 <- coxph(Surv(start, stop, event) ~ x + strata(group), test2b, iter=0)
aeq(3*truth0\$loglik, fit0\$loglik[1])
aeq(3*truth0\$imat, 1/fit0\$var)
aeq(rep(truth0\$mart,3), fit0\$resid)
aeq(rep(truth0\$scho,3),  resid(fit0, 'schoen'))
aeq(rep(truth0\$score,3), resid(fit0, 'score'))

fit3 <- coxph(Surv(start, stop, event) ~x + strata(group), test2b, eps=1e-8)
aeq(3*truth\$loglik, fit3\$loglik[2])
aeq(3*truth\$imat, 1/fit3\$var)
aeq(rep(truth\$mart,3), fit3\$resid)
aeq(rep(truth\$scho,3), resid(fit3, 'schoen'))
aeq(rep(truth\$score,3), resid(fit3, 'score'))

#
# Done with the formal test, now print out lots of bits
#
resid(fit)
resid(fit, 'scor')
resid(fit, 'scho')

predict(fit, type='lp')
predict(fit, type='risk')
predict(fit, type='expected')
predict(fit, type='terms')
predict(fit, type='lp', se.fit=T)
predict(fit, type='risk', se.fit=T)
predict(fit, type='expected', se.fit=T)
predict(fit, type='terms', se.fit=T)

summary(survfit(fit))
summary(survfit(fit, list(x=2)))
```

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survival documentation built on Feb. 16, 2023, 7:34 p.m.