R: Compute jackknife pseudo values.

jackknife {prodlim} | R Documentation

## Compute jackknife pseudo values.

### Description

Compute jackknife pseudo values.

### Usage

    jackknife(object, times, cause, keepResponse = FALSE, ...)

### Arguments

`object` | Object of class `"prodlim"`.
`times` | Time points at which to compute pseudo values.
`cause` | Character (other classes are converted with `as.character`). For competing risks the cause of failure.
`keepResponse` | If `TRUE` add the model response, i.e. event time, event status, etc. to the result.
`...` | not used

### Details

Compute jackknife pseudo values based on marginal Kaplan-Meier estimate of survival, or based on marginal Aalen-Johansen estimate of cumulative incidence.

### Note

The R-package pseudo does a similar job, and appears to be a little faster in small samples, but much slower in large samples. See examples.

### Author(s)

Thomas Alexander Gerds <tag@biostat.ku.dk>

### References

Andersen PK & Perme MP (2010). Pseudo-observations in survival analysis Statistical Methods in Medical Research, 19(1), 71-99.

### See Also

`prodlim`

### Examples

    ## pseudo-values for survival models

    d=SimSurv(20)
    f=prodlim(Hist(time,status)~1,data=d)
    jackknife(f,times=c(3,5))

    ## in some situations it may be useful to attach the
    ## the event time history to the result
    jackknife(f,times=c(3,5),keepResponse=TRUE)

    # pseudo-values for competing risk models
    d=SimCompRisk(10)
    f=prodlim(Hist(time,event)~1,data=d)
    jackknife(f,times=c(3,10),cause=1)
    jackknife(f,times=c(3,10,17),cause=2)

[Package prodlim version 2018.04.18 Index]