Calculate Survival Probabilities
cal_surv_prob.RdComputes individual survival probabilities from a fitted linear predictor
z%*%beta using a stratified Breslow-type baseline hazard estimate.
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.
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.
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)).