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.

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