DunnTest: Dunn's Test for Multiple Comparisons (Non-Parametric)

View source: R/DunnTestNP.R

DunnTestR Documentation

Dunn's Test for Multiple Comparisons (Non-Parametric)

Description

Performs Dunn's test for pairwise comparisons following a Kruskal-Wallis test. Suitable for non-parametric data (ordinal or non-normal), using rank sums. Includes Holm correction by default for multiple comparisons.

Usage

DunnTest(formula, data, alpha = 0.05, method.p = "holm")

Arguments

formula

A formula of the form y ~ group.

data

A data frame containing the variables.

alpha

Significance level (default is 0.05).

method.p

Method for p-value adjustment (default is "holm").

Details

Advantages: - Simple and widely used non-parametric alternative to Tukey's test. - Handles unequal sample sizes. - Compatible with various p-value corrections (e.g., Holm, Bonferroni).

Disadvantages: - Less powerful than DSCF or Conover when sample sizes vary widely. - Requires ranking all data and can be conservative depending on adjustment.

Value

An object of class "dunn" and "comparaciones", including:

  • Resultados: Data frame with group comparisons, z-values, raw and adjusted p-values, and significance.

  • Promedios: Mean ranks of each group.

  • Orden_Medias: Group names ordered from highest to lowest rank.

  • Metodo: "Dunn (no paramétrico)".

References

Dunn, O. J. (1964). Multiple comparisons using rank sums. *Technometrics*, 6(3), 241–252. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00401706.1964.10490181")}

See Also

kruskal.test, dunn.test

Examples

data(d_e, package = "Analitica")
DunnTest(Sueldo_actual ~ labor, data = d_e)



Analitica documentation built on June 14, 2025, 9:07 a.m.