tests/cancer.R

library(survival)

options(na.action=na.exclude) # preserve missings
options(contrasts=c('contr.treatment', 'contr.poly')) #ensure constrast type
aeq <- function(x, y, ...) all.equal(as.vector(x), as.vector(y), ...)

#
# Test out all of the routines on a more complex data set
#
temp <- survfit(Surv(time, status) ~ ph.ecog, lung)
summary(temp, times=c(30*1:11, 365*1:3))
print(temp[2:3])

temp <- survfit(Surv(time, status)~1, lung, type='fleming',
		   conf.int=.9, conf.type='log-log', error='tsiatis')
summary(temp, times=30 *1:5)

temp <- survdiff(Surv(time, status) ~ inst, lung, rho=.5)
print(temp, digits=6)

# verify that the zph routine does the actual score test
dtime <- lung$time[lung$status==2]
lung2 <- survSplit(Surv(time, status) ~ ., lung, cut=dtime)

cfit1 <-coxph(Surv(time, status) ~ ph.ecog + ph.karno + pat.karno + wt.loss 
	      + sex + age + strata(inst), lung) 
cfit2 <-coxph(Surv(tstart, time, status) ~ ph.ecog + ph.karno + pat.karno + 
                  wt.loss + sex + age + strata(inst), lung2) 
all.equal(cfit1$loglik, cfit2$loglik)
all.equal(coef(cfit1), coef(cfit2))

# the above verifies that the data set is correct
zp1 <- cox.zph(cfit1, transform="log")
zp2 <- cox.zph(cfit2, transform="log")
# everything should match but the call
icall <- match("Call", names(zp1))
all.equal(unclass(zp2)[-icall], unclass(zp1)[-icall])

# now compute score tests one variable at a time
ncoef <- length(coef(cfit2))
check <- double(ncoef)
cname <- names(coef(cfit2))
for (i in 1:ncoef) {
    temp <- log(lung2$time) * lung2[[cname[i]]]
    # score test for this new variable
    tfit <- coxph(Surv(tstart, time, status) ~ ph.ecog + ph.karno + pat.karno + 
                  wt.loss + sex + age + strata(inst) +
                  temp, lung2, init=c(cfit2$coef, 0), iter=0)
    check[i] <- tfit$score
    } 
aeq(check, zp1$table[1:ncoef,1]) # skip the 'global' test

#
# Tests of using "."
#
fit1 <- coxph(Surv(time, status) ~ . - meal.cal - wt.loss - inst, lung)
fit2 <- update(fit1, .~. - ph.karno)
fit3 <- coxph(Surv(time, status) ~ age + sex + ph.ecog + pat.karno, lung)
all.equal(fit2, fit3)

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survival documentation built on Aug. 14, 2023, 9:07 a.m.