ANOVA: Analysis of Variance

View source: R/anova_class.R

ANOVAR Documentation

Analysis of Variance


Analysis of Variance (ANOVA) is a univariate method used to analyse the difference among group means. Multiple test corrected p-values are computed to indicate significance for each feature.


ANOVA(alpha = 0.05, mtc = "fdr", formula, ss_type = "III", ...)



(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.


(character) ANOVA sum of squares. Allowed values are limited to the following:

  • "I": Type I sum of squares.

  • "II": Type II sum of squares.

  • "III": Type III sum of squares.

The default is "III".


Additional slots and values passed to struct_class.


This object makes use of functionality from the following packages:

  • car


A ANOVA object with the following output slots:

f_statistic (data.frame) The value of the calculated statistic.
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.


Fox J, Weisberg S (2019). An R Companion to Applied Regression, Third edition. Sage, Thousand Oaks CA.


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

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