logpl: Function to compute the log partial likelihood of a Cox model
In bhklab/survcomp: Performance Assessment and Comparison for Survival Analysis

Description Usage Arguments Value Author(s) References See Also Examples

The function computes the log partial likelihood of a set of coefficients given some survival data.

1	logpl(pred, surv.time, surv.event, strata, na.rm = FALSE, verbose = FALSE)

`surv.time`	vector of times to event occurrence
`surv.event`	vector of indicators for event occurrence
`pred`	linear predictors computed using the Cox model
`strata`	stratification variable
`na.rm`	`TRUE` if the missing values should be removed from the data, `FALSE` otherwise
`verbose`	verbosity of the function

vector of two elements: logpl and event for the estimation of the log partial likelihood and the number of events, respectively

Benjamin Haibe-Kains

Cox, D. R. (1972) "Regression Models and Life Tables", Journal of the Royal Statistical Society Series B, 34, pages 187–220.

coxph, cvpl

set.seed(12345)
age <- rnorm(100, 50, 10)
stime <- rexp(100)
cens <- runif(100,.5,2)
sevent <- as.numeric(stime <= cens)
stime <- pmin(stime, cens)
dd <- data.frame("stime"=stime, "sevent"=sevent, "age"=age)
##Cox model
coxm <- coxph(Surv(stime, sevent) ~ age, data=dd)
##log partial likelihood of the null model
logpl(pred=rep(0, nrow(dd)), surv.time=stime, surv.event=sevent)
##log partial likelihood of the Cox model
logpl(pred=predict(object=coxm, newdata=dd), surv.time=stime, surv.event=sevent)
##equivalent to
coxm$loglik