CI_test | R Documentation |

This function reports the p-values of the tests for non-additivity developed by Boik (1993), Piepho (1994), Kharrati-Kopaei and Sadooghi-Alvandi (2007), Franck et al. (2013), Malik et al. (2016) and Kharrati-Kopaei and Miller (2016). In addition, it combines the p-values of these six tests (and some other available p-values) into a single p-value as a test statistic for testing interaction. There are four combination methods: Bonferroni, Sidak, Jacobi expansion, and Gaussian Copula. The results of these four combined tests are also reported. If there is a significant interaction, the type of interaction is also provided.

CI_test( x, nsim = 10000, nc0 = 10000, opvalue = NULL, alpha = 0.05, report = TRUE, Elapsed_time = TRUE )

`x` |
numeric matrix, |

`nsim` |
a numeric value, the number of Monte Carlo samples for computing an exact Monte Carlo p-value. The default value is 10000. |

`nc0` |
a numeric value, the number of Monte Carlo samples for computing the unbiasing constant |

`opvalue` |
a numeric vector, other p-values (in addition to the six considered p-values) that are going to be combined. |

`alpha` |
a numeric value, the level of the test. The default value is 0.05. |

`report` |
logical: if |

`Elapsed_time` |
logical: if |

The data matrix is divided based on the row of the data matrix for `KKSA_test`

and `Franck_test`

. Note that `KKSA_test`

is not applicable when *a* is less than four. `Franck_test`

and `Piepho_test`

are not applicable when *a* is less than three. This function needs `mvtnorm`

package.

An object of the class `combtest`

, which is a list inducing following components:

`nsim` |
The number of Monte Carlo samples that are used to estimate p-value. |

`Piepho_pvalue` |
The p-value of Piepho's (1994) test. |

`Piepho_Stat` |
The value of Piepho's (1994) test statistic. |

`Boik_pvalue` |
The p-value of Boik's (1993) test. |

`Boik_Stat` |
The value of Boik's (1993) test statistic. |

`Malik_pvalue` |
The p-value of Malik's (2016) et al. test. |

`Malik_Stat` |
The value of Malik's (2016) et al. test statistic. |

`KKM_pvalue` |
The p-value of Kharrati-Kopaei and Miller's (2016) test. |

`KKM_Stat` |
The value of Kharrati-Kopaei and Miller's (2016) test statistic. |

`KKSA_pvalue` |
The p-value of Kharrati-Kopaei and Sadooghi-Alvandi's (2007) test. |

`KKSA_Stat` |
The value of Kharrati-Kopaei and Sadooghi-Alvandi's (2007) test statistic. |

`Franck_pvalue` |
The p-value of Franck's (2013) et al. test. |

`Franck_Stat` |
The value of Franck's (2013) et al. test statistic. |

`Bonferroni` |
The combined p-value by using the Bonferroni method. |

`Sidak` |
The combined p-value by using the Sidak method. |

`Jacobi` |
The combined p-value by using the Jacobi method. |

`GC` |
The combined p-value by using the Gaussian copula. |

`data_name` |
The name of the input dataset. |

`test` |
The name of the test. |

`Level` |
The level of test. |

`Result` |
The result of the combined test at the alpha level with some descriptions on the type of significant interaction. |

Shenavari, Z., Kharrati-Kopaei, M. (2018). A Method for Testing Additivity in Unreplicated Two-Way Layouts Based on Combining Multiple Interaction Tests. International Statistical Review 86(3): 469-487.

data(CNV) CI_test(CNV, nsim = 1000, Elapsed_time = FALSE)

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