cal_surv_prob: Calculate Survival Probabilities

In survkl: Estimate Survival Data with Data Integration

Calculate Survival Probabilities

Description

Computes individual survival probabilities from a fitted linear predictor z%*%beta using a stratified Breslow-type baseline hazard estimate.

Usage

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

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).
beta	A numeric vector of regression coefficients with length equal to the number of columns in z.
stratum	An optional vector specifying the stratum for each observation. If missing, a single-stratum model is assumed.

Details

Inputs are internally sorted by stratum and time. Within each stratum, a baseline hazard increment is computed as delta/S0, where S0 is the risk set sum returned by ddloglik_S0. The stratified baseline cumulative hazard Lambda0 is then formed by a cumulative sum within stratum, and individual survival curves are computed as S(t) = exp(-Lambda0(t) * exp(z %*% beta)).

Value

A numeric matrix of survival probabilities with nrow(z) rows and length(time) columns. Rows correspond to observations; columns are in the internal sorted order of (stratum, time) (i.e., not collapsed to unique event times). Entry S[i, j] is the estimated survival probability for subject i evaluated at the j-th sorted time point.

survkl documentation built on April 22, 2026, 1:08 a.m.