Residuals for Cox proportional hazards models — residual.coxph • Zresidual

Compute several types of residuals (censored Z-residuals, Cox–Snell, martingale, and deviance) for Cox proportional hazards models fitted with coxph.

Usage

residual.coxph(
  fit_coxph,
  newdata,
  residual.type = c("censored Z-residual", "Cox-Snell", "martingale", "deviance")
)

Arguments

fit_coxph: A fitted coxph model object without a shared frailty term. The response should be a right-censored survival object, typically Surv(time, status) or Surv(tstart, tstop, status).
newdata: A data.frame containing the variables required by fit_coxph$formula, including the Surv() response and all covariates. Residuals are evaluated for the observations in newdata.
residual.type: Character string specifying the type of residual to compute. Must be one of "censored Z-residual", "Cox-Snell", "martingale", or "deviance". The default is the full vector c("censored Z-residual", "Cox-Snell", "martingale", "deviance"), but in typical use a single value should be supplied.

Value

A numeric matrix of dimension $n \times 1$, where $n$ is the number of observations in newdata. The single column is named according to residual.type. Several attributes are attached:

Survival.Prob: vector of survival probabilities $S_i(t_i)$.
linear.pred: vector of linear predictors $\eta_i$.
covariates: model matrix of covariates (columns used in the linear predictor).
censored.status: event indicator (1 = event, 0 = censored).
object.model.frame: the model.frame constructed from fit_coxph$formula and newdata.

Examples

if (FALSE) { # \dontrun{
  library(survival)

  data(lung)

  ## Cox PH model
  fit_cox <- coxph(Surv(time, status) ~ age + sex, data = lung)

  ## Censored Z-residuals
  r_z <- residual.coxph(fit_cox, newdata = lung,
                        residual.type = "censored Z-residual")

  ## Cox–Snell residuals
  r_cs <- residual.coxph(fit_cox, newdata = lung,
                         residual.type = "Cox-Snell")

  ## Martingale residuals
  r_m <- residual.coxph(fit_cox, newdata = lung,
                        residual.type = "martingale")

  ## Deviance residuals
  r_d <- residual.coxph(fit_cox, newdata = lung,
                        residual.type = "deviance")
} # }