HSD: Tukey's Honest Significant Difference

View source: R/HSD_class.R

HSDR Documentation

Tukey's Honest Significant Difference


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.


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



(numeric) The p-value cutoff for determining significance. The default is 0.05.


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


(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.


This object makes use of functionality from the following packages:

  • agricolae


A HSD object with the following output slots:

difference (data.frame)
UCL (data.frame)
LCL (data.frame)
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.


de Mendiburu F (2021). agricolae: Statistical Procedures for Agricultural Research. R package version 1.3-5, https://CRAN.R-project.org/package=agricolae.


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

computational-metabolomics/structToolbox documentation built on Feb. 6, 2023, 2:43 p.m.