Calculate the Log-Partial Likelihood for a Stratified Cox Model

Computes the stratified Cox partial log-likelihood for given covariates, event indicators, times, and coefficients.

Usage

loss_fn(z, delta, time, stratum, beta)

Arguments

z

A numeric matrix (or data frame coercible to matrix) of covariates. Each row is an observation and each column a predictor.

delta

A numeric vector of event indicators (1 = event, 0 = censored).

time

A numeric vector of observed times (event or censoring).

stratum

An optional vector specifying the stratum for each observation (factor/character/numeric). If missing, a single-stratum model is assumed.

beta

A numeric vector of regression coefficients with length equal to the number of columns in z.

Value

A single numeric value giving the stratified Cox partial log-likelihood.

Details

Inputs are internally sorted by stratum and time. The function evaluates the stratified Cox partial log-likelihood using the supplied z, delta, beta, and the stratum sizes.