`R/pseudo-modules.R`

`pseudo_independent.Rd`

Assuming completely independent censoring, i.e., censoring does not depend on the survival time nor any covariates in the model, the pseudo observations are calculated with the standard jackknife approach

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

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. |
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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 | Not used with this method, see pseudo_stratified, pseudo_aareg or pseudo_coxph |

ipcw.method | Not used with this method |

A vector of jackknife pseudo observations

POi <- pseudo_independent(Surv(time, status) ~ 1, 1500, cause = 1, data = colon, type = "survival") mean(POi)#> [1] 0.5980774