HSD {structToolbox} | R Documentation

## Tukey's Honest Significant Difference

### Description

Tukey's HSD post hoc test is a modified t-test applied for all features to all pairs of levels in a factor. It is used to determine which groups are different (if any). A multiple test corrected p-value is computed to indicate which groups are significantly different to the others for each feature.

### Usage

    HSD(alpha = 0.05, mtc = "fdr", formula, unbalanced = FALSE, ...)

### 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.
`unbalanced` | (logical) Unbalanced model. Allowed values are limited to the following: `"TRUE"`: A correction is applied for unbalanced designs. `"FALSE"`: No correction is applied for unbalanced designs. The default is `FALSE`.
`...` | Additional slots and values passed to `struct_class`.

### Details

This object makes use of functionality from the following packages:

- `agricolae`

### Value

A `HSD` object.

### References

de Mendiburu F (2020). agricolae: Statistical Procedures for Agricultural Research. R package version 1.3-3, https://CRAN.R-project.org/package=agricolae.

### Examples

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

[Package structToolbox version 1.2.0 Index]