DuncanTest: Duncan Multiple Range Test (DMRT)

View source: R/DuncanTest.R

DuncanTestR Documentation

Duncan Multiple Range Test (DMRT)

Description

Performs the Duncan test for pairwise comparisons after an ANOVA. This method is more liberal than Tukey's HSD, using a stepwise approach with critical values from the studentized range distribution.

Usage

DuncanTest(modelo, alpha = 0.05)

Arguments

modelo

An object of class aov or lm.

alpha

Significance level (default is 0.05).

Details

Advantages: - High power for detecting differences. - Simple to interpret and implement.

Disadvantages: - Inflates Type I error rate. - Not recommended for confirmatory research.

Value

An object of class "duncan" and "comparaciones", containing:

  • Resultados: A data frame with pairwise comparisons, mean differences, critical values, p-values, and significance indicators.

  • Promedios: A named numeric vector of group means.

  • Orden_Medias: A character vector with group names ordered from highest to lowest mean.

  • Metodo: A character string indicating the comparison method ("Duncan").

References

Duncan, D. B. (1955). "Multiple range and multiple F tests." Biometrics, 11(1), 1-42.

Examples

data(d_e, package = "Analitica")
mod <- aov(Sueldo_actual ~ as.factor(labor), data = d_e)
resultado <- DuncanTest(mod)
summary(resultado)
plot(resultado)

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