Description Usage Arguments Value References Examples

This function calculates the sample size for a given power, type-I error rate and allocation rate t = n_1/N. Additionally, the actual achieved power can be simulated.

1 2 |

`x` |
prior information for the first group |

`y` |
prior information for the second group |

`alpha` |
two sided type I error rate |

`power` |
power |

`t` |
proportion of subjects in the first group; or use t = "min" to use optimal proportion rate |

`simulation` |
TRUE if a power simulation should be carried out |

`nsim` |
number of simulations for the power simulation |

Returns an object from class WMWssp containing

`result` |
A dataframe with the results. |

`t` |
The allocation rate which was used. |

`alpha` |
The type-I error rate which was used. |

`simulation` |
The achieved power in a simulation. |

`power` |
The power which was used. |

`N` |
The sample size needed. |

Brunner, E., Bathke A. C. and Konietschke, F. Rank- and Pseudo-Rank Procedures in Factorial Designs - Using R and SAS. Springer Verlag. to appear.

Happ, M., Bathke, A. C., & Brunner, E. (2019). Optimal Sample Size Planning for the Wilcoxon-Mann-Whitney-Test. Statistics in medicine, 38(3), 363-375.

1 2 3 4 5 6 7 8 |

```
Wilcoxon-Mann-Whitney Sample Size Calculation
Summary
Call: WMWssp
Type-I error (two-sided): 0.05
Power: 0.8
Results
alpha (2-sided) 0.0500000
Power 0.8000000
Estimated relative effect p 0.3491124
N (total sample size needed) 111.3719511
t=n1/N 0.5000000
n1 in Group 1 55.6859755
n2 in Group 2 55.6859755
N rounded 112.0000000
n1 rounded 56.0000000
n2 rounded 56.0000000
```

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