Description Usage Arguments Value Examples

`ttest.pexplore`

computes (via simulation) the power of an experiment that will be analyzed using a u test (also called Wilcoxon test) for a range of sample sizes.
Rather than taking a theoretical distribution, this function takes empirical data and bootstraps them to calculate the power.

1 2 3 | ```
utest.pexplore(x, y = NULL, lown, topn, r = 10000,
alternative = c("two.sided", "less", "greater"), mu = NULL,
alpha = 0.05, plotit = TRUE, conf.level = 0.95)
``` |

`lown` |
smallest sample size to explore. |

`topn` |
largest sample size to explore. |

`plotit` |
logical (default= |

The probability of finding *p < α* with the experiment description.

1 2 3 | ```
utest.pexplore(x=c(0, 5, 10), lown=16, topn=24) # Power for a one-sample u test with n in 16-24. Pilot data consists of three data points.
utest.pexplore(x=c(0, 5, 10), lown=16, topn=24,mu = -5) # Same as above, changing the avarege under the null to -5.
utest.pexplore(x=c(0, 5, 10), lown=16, topn=24, y=c(9, 3, 2, 1)) # Power for a two-sample u test with n=16-24 (per condition) using unbalanced pilot data.
``` |

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