HSD: Tukey's Honest Significant Difference

Description Usage Arguments Details Value References Examples

View source: R/HSD_class.R

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

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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:

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

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

structToolbox documentation built on Nov. 8, 2020, 6:54 p.m.