ANOVA | R Documentation |

Analysis of Variance (ANOVA) is a univariate method used to analyse the difference among group means. Multiple test corrected p-values are computed to indicate significance for each feature.

ANOVA(alpha = 0.05, mtc = "fdr", formula, ss_type = "III", ...)

`alpha` |
(numeric) The p-value cutoff for determining significance. The default is |

`mtc` |
(character) Multiple test correction method. Allowed values are limited to the following: `"bonferroni"` : Bonferroni correction in which the p-values are multiplied by the number of comparisons.`"fdr"` : Benjamini and Hochberg False Discovery Rate correction.`"none"` : No correction.
The default is |

`formula` |
(formula) A symbolic description of the model to be fitted. |

`ss_type` |
(character) ANOVA sum of squares. Allowed values are limited to the following: `"I"` : Type I sum of squares.`"II"` : Type II sum of squares.`"III"` : Type III sum of squares.
The default is |

`...` |
Additional slots and values passed to |

This object makes use of functionality from the following packages:

`car`

A `ANOVA`

object with the following `output`

slots:

`f_statistic` | (data.frame) The value of the calculated statistic. |

`p_value` | (data.frame) The probability of observing the calculated statistic if the null hypothesis is true. |

`significant` | (data.frame) True/False indicating whether the p-value computed for each variable is less than the threshold. |

Fox J, Weisberg S (2019).
*An R Companion to Applied Regression*, Third edition.
Sage, Thousand Oaks CA.
https://socialsciences.mcmaster.ca/jfox/Books/Companion/.

D = iris_DatasetExperiment() M = ANOVA(formula=y~Species) M = model_apply(M,D)

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