View source: R/manylabRs_SOURCE.R

get.ncpCI

get.ncpCI

get.ncpCI

1 2 3 4 5 6 7 8 | ```
get.ncpCI(x, df1, df2, N, esType, CL = 0.95, keepSign = TRUE,
keepDirection = TRUE, alternative = "two.sided")
get.ncpCI(x, df1, df2, N, esType, CL = 0.95, keepSign = TRUE,
keepDirection = TRUE, alternative = "two.sided")
get.ncpCI(x, df1, df2, N, esType, CL = 0.95, keepSign = TRUE,
keepDirection = TRUE, alternative = "two.sided")
``` |

`x` |
A noncentrality parameter. |

`df1` |
Degrees of freeddom. |

`df2` |
NULL or degrees of freedom of the denominator for the f-distribution. |

`N` |
Sample size |

`esType` |
Type of test statistic. One of: "t", "t.r", lm.t", "f", "lm.f", "r", "X2", "Z", "lm.Z" |

`CL` |
Confidence Limit (default: .95). |

`keepSign` |
Return effect size with sign of test statistic? (default = TRUE). |

`keepDirection` |
Use the information in |

`alternative` |
Alternative hypothesis (defult = "two"). |

`x` |
A noncentrality parameter. |

`df1` |
Degrees of freeddom. |

`df2` |
NULL or degrees of freedom of the denominator for the f-distribution. |

`N` |
Sample size |

`esType` |
Type of test statistic. One of: "t", "t.r", lm.t", "f", "lm.f", "r", "X2", "Z", "lm.Z" |

`CL` |
Confidence Limit (default: .95). |

`keepSign` |
Return effect size with sign of test statistic? (default = TRUE). |

`keepDirection` |
Use the information in |

`alternative` |
Alternative hypothesis (defult = "two"). |

`x` |
A noncentrality parameter. |

`df1` |
Degrees of freeddom. |

`df2` |
NULL or degrees of freedom of the denominator for the f-distribution. |

`N` |
Sample size |

`esType` |
Type of test statistic. One of: "t", "t.r", lm.t", "f", "lm.f", "r", "X2", "Z", "lm.Z" |

`CL` |
Confidence Limit (default: .95). |

`keepSign` |
Return effect size with sign of test statistic? (default = TRUE). |

`keepDirection` |
Use the information in |

`alternative` |
Alternative hypothesis (defult = "two"). |

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