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

In structToolbox: Data processing & analysis tools for Metabolomics and other omics

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.

References

Lenth R (2020). emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.5.2-1, https://CRAN.R-project.org/package=emmeans.

Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2020). nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1-149, https://CRAN.R-project.org/package=nlme.

Examples

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)

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