TukeyTest: Tukey HSD Test for Multiple Comparisons

In Analitica: Exploratory Data Analysis and Group Comparison Tools

Tukey HSD Test for Multiple Comparisons

Description

Performs Tukey's Honest Significant Difference (HSD) test for all pairwise comparisons after fitting an ANOVA model. This post hoc method uses the studentized range distribution and is appropriate when variances are equal across groups and observations are independent.

Usage

TukeyTest(modelo, alpha = 0.05)

Arguments

modelo	An object of class aov or lm representing an ANOVA model.
alpha	Significance level (default is 0.05).

Details

Tukey's test controls the family-wise error rate and is widely used when group comparisons have not been planned in advance.

Advantages: - Strong control of Type I error rate. - Ideal for balanced designs with equal variances.

Disadvantages: - Assumes equal variances and sample sizes. - Less powerful with heteroscedasticity.

Value

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

• Resultados: A data frame of pairwise comparisons with mean differences, critical value, p-value, and significance level.

• 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 method used ("Tukey").

References

Tukey, J. W. (1949). "Comparing individual means in the analysis of variance." Biometrics, 5(2), 99–114. <https://doi.org/10.2307/3001913>

Examples

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

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