Description Usage Arguments Details Value Note Author(s) References Examples

View source: R/Functions_Rsurrogate.R

This function calculates the robust estimate of the residual treatment effect accounting for surrogate marker information measured at *t_0* and primary outcome information up to *t_0* i.e. the hypothetical treatment effect if both the surrogate marker distribution at *t_0* and survival up to *t_0* in the treatment group look like the surrogate marker distribution and survival up to *t_0* in the control group. Ideally this function is only used as a helper function and is not directly called.

1 2 |

`xone` |
numeric vector, the observed event times in the treatment group, X = min(T,C) where T is the time of the primary outcome and C is the censoring time. |

`xzero` |
numeric vector, the observed event times in the control group, X = min(T,C) where T is the time of the primary outcome and C is the censoring time. |

`deltaone` |
numeric vector, the event indicators for the treatment group, D = I(T<C) where T is the time of the primary outcome and C is the censoring time. |

`deltazero` |
numeric vector, the event indicators for the control group, D = I(T<C) where T is the time of the primary outcome and C is the censoring time. |

`sone` |
numeric vector; surrogate marker measurement at |

`szero` |
numeric vector; surrogate marker measurement at |

`t` |
the time of interest. |

`weight.perturb` |
weights used for perturbation resampling. |

`landmark` |
the landmark time |

`extrapolate` |
TRUE or FALSE; indicates whether the user wants to use extrapolation. |

`transform` |
TRUE or FALSE; indicates whether the user wants to use a transformation for the surrogate marker. |

Details are included in the documentation for R.s.surv.estimate.

*\hat{Δ}_S(t,t_0)*, the robust residual treatment effect estimate accounting for surrogate marker information measured at *t_0* and primary outcome information up to *t_0*.

If the treatment effect is not significant, the user will receive the following message: "Warning: it looks like the treatment effect is not significant; may be difficult to interpret the residual treatment effect in this setting". If the treatment effect is negative, the user will receive the following message: "Warning: it looks like you need to switch the treatment groups" as this package assumes throughout that larger values of the event time are better. If the observed support of the surrogate marker for the control group is outside the observed support of the surrogate marker for the treatment group, the user will receive the following message: "Warning: observed supports do not appear equal, may need to consider a transformation or extrapolation".

Layla Parast

Parast L, Cai T and Tian L. Evaluating Surrogate Marker Information using Censored Data. Under Review.

1 2 |

Rsurrogate documentation built on May 29, 2017, 6:16 p.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.