Efron's l/d weighting shrinks the risk set progressively across the
d tied events, which approximates the exact discrete likelihood at
essentially Breslow's cost. With no ties the two coincide exactly –
a useful test, and one the parity suite asserts.
Usage
morie_efron_tie_correction(time, event, X, ...)
Arguments
- time
follow-up times, non-negative.
- event
1 for an event, 0 for right-censored.
- X
covariate matrix, one row per subject.
- ...
passed to the fitter (max_iter, tol,
offset).
References
Efron, B. (1977). The efficiency of Cox's likelihood
function for censored data. JASA, 72(359), 557-565.
Examples
set.seed(1)
X <- matrix(rnorm(120), ncol = 2)
tt <- round(rexp(60, exp(X %*% c(0.7, -0.4))), 1) # ties on purpose
morie_efron_tie_correction(tt, rep(1, 60), X)$beta
#> [1] 0.6941003 -0.5302356
