ScheffeTest: Scheffe Test for Multiple Comparisons v2.0

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

Scheffe Test for Multiple Comparisons v2.0

Description

Performs Scheffe's post hoc test after fitting an ANOVA model. This test compares all possible pairs of group means, using a critical value based on the F-distribution.

Usage

ScheffeTest(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

The Scheffe test is a conservative method, making it harder to detect significant differences, but reducing the likelihood of Type I errors (false positives). It is especially appropriate when the comparisons were not pre-planned and the number of contrasts is large.

Assumptions: normally distributed residuals and homogeneity of variances.

Advantages: - Very robust to violations of assumptions. - Suitable for complex comparisons, not just pairwise.

Disadvantages: - Very conservative; reduced power. - Not ideal for detecting small differences.

Value

Objeto de clase "scheffe" and "comparaciones" with:

• Resultados: data.frame with Comparacion, Diferencia, SE2 (= MSerror*(1/n_i+1/n_j)), F_obs, Valor_Critico, p_value, Significancia.

• Promedios, Orden_Medias, Metodo="Scheffe", Termino.

• MSerror, df_error, N (utiles para plot.comparaciones()).

References

Scheffe, H. (1953). "A method for judging all contrasts in the analysis of variance." Biometrika, 40(1/2), 87–104. <https://doi.org/10.1093/biomet/40.1-2.87>

Examples

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

# RCBD
mod <- aov(Sueldo_actual ~ as.factor(labor) + Sexo, data = d_e)
res <- ScheffeTest(mod, comparar = "as.factor(labor)")
summary(res); plot(res)                      # plot usara p_value

# Factorial
mod2 <- aov(Sueldo_actual ~ as.factor(labor) * Sexo, data = d_e)
resAB <- ScheffeTest(mod2, comparar = c("as.factor(labor)","Sexo"))
summary(resAB, n = Inf); plot(resAB, horizontal = TRUE)

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