ANOVA {structToolbox} | R Documentation

## Analysis of Variance

### Description

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.

### Usage

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

### Arguments

`alpha` | (numeric) The p-value cutoff for determining significance. The default is `0.05`.
`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 `"fdr"`.
`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 `"III"`.
`...` | Additional slots and values passed to `struct_class`.

### Details

This object makes use of functionality from the following packages:

- `car`

### Value

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.

### References

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

### Examples

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

[Package structToolbox version 1.6.1 Index]