pairwise_test {CNPS} | R Documentation |

Detects differences between two related samples.

pairwise_test(x, y, alternative = "greater", score = "wilcoxon", method_p = "asymptotic", method_asymptotic = "norm", method_wilcoxon = "type1", samplenum = 1000, conf.level.sample = 0.95, samplemethod = "R")

`x` |
numeric vectors of data values and should have the same length |

`y` |
numeric vectors of data values and should have the same length |

`alternative` |
a character string specifying the alternative hypothesis, must be one of "two.sided", "greater"(default) or "less" |

`score` |
determines scoring systems and must be one of "original", "wilcoxon" or "sign" |

`method_p` |
a string indicating what method to use for p-value. "sampling" represents sampling; "asymptotic" represents using large sample approximations; "exact" represents Iterate through all combinations |

`method_asymptotic` |
determines the asymptotic distribution and should be one of "norm" or "binomial"(only for method_p="sign") |

`method_wilcoxon` |
indicates the way to compute wilcoxon ranks when the ties are 0 and could be one of "type1" or "type2" |

`samplenum` |
the number of SRS samples |

`conf.level.sample` |
p-value confidence level for SRS sampling |

`samplemethod` |
a discrete value indicating the method of sampling. "S" represents sample function sampling; "R" represents Put-back sampling |

If score="sign", then method_p must be "asymptotic". Three scoring systems can use the normal approximation but only "sign" can use binomial approximation. Namely, the argument method_asymptotic can be selected as "binomial" only if method_p="sign". And method_wilcoxon indicates the method to deal with ties. "type1" means ranking with zeros and "type2" means ranking without zeros.

A list with following components

`method` |
the test uesd |

`score` |
the score which is used |

`stat` |
the statistic of the data under the given scoring system |

`conf.int` |
the confidence interval for p-value(only if method_p = "sampling") |

`pval` |
p-value for the test |

`null.value` |
a character string describing the alternative hypothesis |

Jiasheng Zhang, Feng Yu, Yangyang Zhang, Siwei Deng. Tutored by YuKun Liu and Dongdong Xiang.

Higgins, J. J. (2004). An introduction to modern nonparametric statistics. Pacific Grove, CA: Brooks/Cole.

x1=c(1530, 2130,2940,1960,2270) x2=c(1290, 2250,2430,1900,2120) pairwise_test(x1 , x2) pairwise_test(x1 , x2 , method_p = "sampling" , samplenum = 4000) pairwise_test(x1 , x2 , method_p = "asymptotic" , method_asymptotic = "norm")

[Package *CNPS* version 1.0.0 Index]