HSDEM: Tukey's Honest Significant Difference using estimated...

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

Tukey's Honest Significant Difference using estimated marginal means

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. For mixed effects models estimated marginal means are used.

Usage

HSDEM(alpha = 0.05, mtc = "fdr", formula, ...)

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.
...	Additional slots and values passed to struct_class.

Details

This object makes use of functionality from the following packages:

• emmeans

• nlme

Value

A HSDEM object with the following output slots:

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 HSDEM object inherits the following struct classes:

⁠[HSDEM]⁠ >> ⁠[model]⁠ >> ⁠[struct_class]⁠

References

Lenth R (2023). emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.9.0, https://CRAN.R-project.org/package=emmeans.

Pinheiro J, Bates D, R Core Team (2023). nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1-164, https://CRAN.R-project.org/package=nlme.

Pinheiro JC, Bates DM (2000). Mixed-Effects Models in S and S-PLUS. Springer, New York. doi:10.1007/b98882 https://doi.org/10.1007/b98882.

Examples

M = HSDEM(
      alpha = 0.05,
      mtc = "fdr",
      formula = y ~ x)

D = iris_DatasetExperiment()
D$sample_meta$id=rownames(D) # dummy id column
M = HSDEM(formula = y~Species+ Error(id/Species))
M = model_apply(M,D)

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