powerBuyseTest {BuyseTest} | R Documentation |

Performs a simulation studies for several sample sizes. Returns estimates, standard errors, confidence intervals and p.values.

powerBuyseTest( sim, sample.size, sample.sizeC = NULL, sample.sizeT = NULL, n.rep, null = c(netBenefit = 0), cpus = 1, seed = NULL, conf.level = NULL, alternative = NULL, order.Hprojection = NULL, transformation = NULL, trace = 1, ... )

`sim` |
[function] take two arguments:
the sample size in the control group ( |

`sample.size` |
[integer vector, >0] the various sample sizes at which the simulation should be perform.
Disregarded if any of the arguments |

`sample.sizeC` |
[integer vector, >0] the various sample sizes in the control group. |

`sample.sizeT` |
[integer vector, >0] the various sample sizes in the treatment group. |

`n.rep` |
[integer, >0] the number of simulations. |

`null` |
[numeric vector] For each statistic of interest, the null hypothesis to be tested. The vector should be named with the names of the statistics. |

`cpus` |
[integer, >0] the number of CPU to use. Default value is 1. |

`seed` |
[integer, >0] the seed to consider for the simulation study. |

`conf.level` |
[numeric] confidence level for the confidence intervals.
Default value read from |

`alternative` |
[character] the type of alternative hypothesis: |

`order.Hprojection` |
[integer 1,2] the order of the H-project to be used to compute the variance of the net benefit/win ratio.
Default value read from |

`transformation` |
[logical] should the CI be computed on the logit scale / log scale for the net benefit / win ratio and backtransformed.
Otherwise they are computed without any transformation.
Default value read from |

`trace` |
[integer] should the execution of the function be traced? |

`...` |
other arguments (e.g. |

Brice Ozenne

library(data.table) #### Using simBuyseTest #### ## only point estimate powerBuyseTest(sim = simBuyseTest, sample.size = c(10, 50, 100), n.rep = 10, formula = treatment ~ bin(toxicity), seed = 10, method.inference = "none", trace = 2) ## point estimate with rejection rate powerBuyseTest(sim = simBuyseTest, sample.size = c(10, 50, 100), n.rep = 10, formula = treatment ~ bin(toxicity), seed = 10, method.inference = "u-statistic", trace = 4) #### Using user defined simulation function #### ## Example of power calculation for Wilcoxon test simFCT <- function(n.C, n.T){ out <- rbind(cbind(Y=stats::rt(n.C, df = 5), group=0), cbind(Y=stats::rt(n.T, df = 5), group=1) + 1) return(data.table::as.data.table(out)) } ## Not run: powerW <- powerBuyseTest(sim = simFCT, sample.size = c(5, 10,20,30,50,100), n.rep = 1000, formula = group ~ cont(Y), cpus = "all") summary(powerW) ## End(Not run)

[Package *BuyseTest* version 2.3.0 Index]