DuncanTest: Duncan Multiple Range Test (DMRT) v2.0

In Analitica: Exploratory Data Analysis, Group Comparison Tools, and Other Procedures

Duncan Multiple Range Test (DMRT) v2.0

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, comparar = NULL, alpha = 0.05)

Arguments

modelo	An aov or lm object (full model: includes blocks, factors, etc.).
comparar	Character vector with the name(s) of the factor(s) to compare: - One name: main effect (e.g., "treatment" or "A") - Several names: interaction (e.g., c("A","B") for A:B) If omitted, it uses the first factor in modelo$xlevels.
alpha	Significance level (default 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 columns Comparacion, Diferencia, SE, t_value, p_value (unadjusted), p_ajustada (duncan), Valor_Critico (critical difference), and Significancia.

• Promedios: a named vector of group means as defined by comparar.

• Orden_Medias: group names ordered from highest to lowest mean.

• Metodo: "Duncan t-test".

• Termino: the term being compared (e.g., "A", "B", or "A:B").

• MSerror, df_error, N: useful for plots with error bars.

References

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

Examples

# DCA
data(d_e, package = "Analitica")
mod1 <- aov(Sueldo_actual ~ as.factor(labor), data = d_e)
resultado <- DuncanTest(mod1)
summary(resultado)
plot(resultado)

# DBA
mod2 <- aov(Sueldo_actual ~ as.factor(labor) + Sexo, data = d_e)
res <- DuncanTest(mod2, comparar = "as.factor(labor)")
summary(res); plot(res)

# DFactorial
mod3 <- aov(Sueldo_actual ~as.factor(labor) * Sexo, data = d_e)
resAB <- DuncanTest(mod3, comparar = c("as.factor(labor)","Sexo"))  # celdas A:B
summary(resAB, n = Inf); plot(resAB, horizontal = TRUE)

Analitica documentation built on Nov. 5, 2025, 5:13 p.m.