Compute pseudo observations using stratified jackknife

Assuming that the censoring depends on covariates with a finite set of levels, the pseudo observations are calculated with the jackknife approach stratified on those covariates.

Usage

pseudo_stratified(
  formula,
  time,
  cause = 1,
  data,
  type = c("cuminc", "survival", "rmean"),
  formula.censoring = NULL,
  ipcw.method = NULL
)

Arguments

formula: A formula specifying the model. The left hand side must be a Surv object specifying a right censored survival or competing risks outcome. The status indicator, normally 0=alive, 1=dead. Other choices are TRUE/FALSE (TRUE = death) or 1/2 (2=death). For competing risks, the event variable will be a factor, whose first level is treated as censoring. The right hand side is the usual linear combination of covariates.
time: Numeric constant specifying the time at which the cumulative incidence or survival probability effect estimates are desired.
cause: Numeric or character constant specifying the cause indicator of interest.
data: Data frame in which all variables of formula can be interpreted.
type: One of "survival", "cuminc", or "rmean"
formula.censoring: A right-sided formula specifying which variables to stratify on. All variables in this formula must be categorical.
ipcw.method: Not used with this method

Value

A vector of jackknife pseudo observations

Examples

POi <- pseudo_stratified(Surv(time, status) ~ 1, 1500, cause = 1,
  data = colon, formula.censoring = ~ sex, type = "rmean")
mean(POi)
#> [1] 1180.518