Description Usage Arguments Details Value References See Also Examples

View source: R/mdir.onesided.R

The mdir.onesided function calculates the multiple-direction logrank statistic for (one-sided) stochastic ordered alternatives and its p-value based on a wild bootstrap approach

1 2 3 |

`data` |
A data.frame, list or environment containing the variables |

`group1` |
The name or the coding for the first group in the data set (neceassary for a one-sided testing problem). |

`rg` |
A list containing the exponents |

`w.user` |
A list containing the user specified functions or |

`wild` |
The wild bootstrap approach used for estimating the p-value. The Rademacher
( |

`iter` |
The number of iteration used for calculating the wild bootstrap p-value. The default option is 10000. |

`dig_p` |
The p-values are rounded to |

`dig_stat` |
The test statistic is rounded to |

The function provides the multiple-direction logrank statistic for
the two sample one-sided testing problem of stochastic ordering within right-censored survival data.
The null hypothesis *H:F_1=F_2* is tested against the one-sided alternative *K:F_1 ≥ F_2,
F_1 \neq F_2*. The first group corresponding to *F_1* can be specified
by the argument `group1`

. An arbitrary amount of directions/weights of the form
*w(x) = x^r (1-x)^g* for natural numbers r,g (including 0) can be chosen in the list
`rg`

. The multiple-direction onesided logrank test needs linearly independent directions.
A check for this is implemented. If the directions chosen by the user are
linearly dependent then a subset consisting of linearly independent directions
is selected automatically. The user can also specify weights of a different shape in the list
`w.user`

. But if the user specified own weights in `w.user`

then there is no
automatic check for linear independence.

The `mdir.onesided`

function returns the test statistic and the p-value
based on a wild bootstrap procedure `wild`

.

An `mdirone`

object containing the following components:

`Descriptive` |
The directions used and whether the directions specified by the user were linearly independent. |

`p.value` |
The p-value of the one-sided multiple-direction logrank test using the the using the permutation approach (Perm.). |

`wild` |
The wild bootstrap approach which was used |

`stat` |
Value of the one-sided multiple-direction logrank statistic. |

`rg` |
The argument |

`w.user` |
The argument |

`group1` |
The name of the first group. |

`indep` |
logical or NA. |

`iter` |
The number of iterations used for calculating the wild bootstrap p-value. |

Ditzhaus, M., Pauly, M. (2018). Wild bootstrap logrank tests with broader power functions for testing superiority. arXiv preprint arXiv:arXiv:1808.05627.

1 2 3 4 5 6 | ```
library(coin)
data(GTSG)
out <- mdir.onesided(data = GTSG, group1 = "Chemotherapy+Radiation", iter = 1000)
## Detailed information:
summary(out)
``` |

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