HSD: Tukey's Honest Significant Difference

In computational-metabolomics/structtoolbox: Data processing & analysis tools for Metabolomics and other omics

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 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.

Inheritance

A HSD object inherits the following struct classes:

⁠[HSD]⁠ >> ⁠[model]⁠ >> ⁠[struct_class]⁠

References

de Mendiburu F (2023). agricolae: Statistical Procedures for Agricultural Research. R package version 1.3-7, https://CRAN.R-project.org/package=agricolae.

Examples

M = HSD(
      alpha = 0.05,
      mtc = "fdr",
      formula = y ~ x,
      unbalanced = FALSE)

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

computational-metabolomics/structtoolbox documentation built on Feb. 9, 2024, 8:19 a.m.