BonferroniTest: Bonferroni-Corrected Pairwise t-Tests

In Analitica: Exploratory Data Analysis and Group Comparison Tools

Bonferroni-Corrected Pairwise t-Tests

Description

Performs pairwise t-tests with Bonferroni adjustment for multiple comparisons. This method controls the family-wise error rate by dividing the alpha level by the number of comparisons.

Usage

BonferroniTest(modelo, alpha = 0.05)

Arguments

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

Details

Advantages: - Very simple and easy to implement. - Strong control of Type I error. - Applicable to any set of independent comparisons.

Disadvantages: - Highly conservative, especially with many groups. - Can lead to low statistical power (increased Type II error). - Does not adjust test statistics, only p-values.

Value

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

• Resultados: Data frame with comparisons, mean differences, t-values, unadjusted and adjusted p-values, and significance.

• Promedios: Named numeric vector of group means.

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

• Metodo: Name of the method used ("Bonferroni-adjusted t-test").

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")}

Wilcoxon, F. (1945). Individual Comparisons by Ranking Methods. Biometrics Bulletin, 1(6), 80–83. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/3001968")}

Examples

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

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