Description Usage Arguments Value Note Author(s) References See Also Examples

View source: R/npar.t.test.paired.r

The function npar.t.test.paired performs a two sample studentized permutation test for paired data, that is testing the hypothesis

*H0: p=1/2,*

where p denotes the relative effect of 2 dependent samples, and computes a confidence interval for the relative effect p. In addition the Brunner-Munzel-Test accompanied by a confidence interval for the relative effect is implemented. npar.t.test.paired also computes one-sided and two-sided confidence intervals and p-values. The confidence interval can be plotted.

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`formula` |
A two-sided 'formula' specifying a numeric response variable and a factor with two levels. If the factor contains more than two levels, an error message will be returned. |

`data` |
A dataframe containing the variables specified in formula. |

`conf.level` |
The confidence level (default is 0.95). |

`alternative` |
Character string defining the alternative hypothesis, one of "two.sided", "less" or "greater". |

`nperm` |
The number of permutations for the studentized permutation test. By default it is nperm=10,000. |

`rounds` |
Number of rounds for the numeric values of the output (default is 3). |

`info` |
A logical whether you want a brief overview with informations about the output. |

`plot.simci` |
A logical indicating whether you want a plot of the confidence interval. |

` Info ` |
List of samples and sample sizes. |

`Analysis ` |
Effect: relative effect p(a,b) of the two samples 'a' and 'b', p.hat: estimated relative effect, Lower: Lower limit of the confidence interval, Upper: Upper limit of the confidence interval, T: studentized teststatistic p.value: p-value for the hypothesis. |

` input ` |
List of input by user. |

A summary and a graph can be created separately by using the functions
`summary.nparttestpaired`

and `plot.nparttestpaired`

.

Make sure that your dataset is ordered by subjects before applying npar.t.test.paired.

Frank Konietschke

Munzel, U., Brunner, E. (2002). An Exact Paired Rank Test. Biometrical Journal 44, 584-593.

Konietschke, F., Pauly, M. (2012). A Studentized Permutation Test for the Nonparametric Behrens-Fisher Problem in Paired Data. Electronic Journal of Statistic, Vol 6, 1358-1372.

For multiple comparison procedures based on relative effects, see `nparcomp`

.

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nparcomp documentation built on May 29, 2017, 2:43 p.m.

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