DSCFTest: Dwass-Steel-Critchlow-Fligner (DSCF) Test (Non-Parametric)

In Analitica: Exploratory Data Analysis and Group Comparison Tools

Dwass-Steel-Critchlow-Fligner (DSCF) Test (Non-Parametric)

Description

Robust non-parametric method for multiple comparisons after Kruskal-Wallis. Uses rank-based pairwise tests with a pooled variance estimate.

Usage

DSCFTest(formula, data, alpha = 0.05, method.p = "holm")

Arguments

formula	A formula of the form y ~ group.
data	A data frame containing the variables.
alpha	Significance level (default is 0.05).
method.p	Method for p-value adjustment (default is "holm").

Details

Advantages: - Strong control of Type I error with unequal sample sizes. - More powerful than Dunn in many conditions.

Disadvantages: - Computationally more complex. - Less commonly available in standard software.

Value

An object of class "dscf" and "comparaciones", including:

• Resultados: Data frame with comparisons, z-statistics, p-values, adjusted p-values, and significance levels.

• Promedios: Mean ranks of each group.

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

• Metodo: "DSCF (no paramétrico)".

References

Dwass, M. (1960). Some k-sample rank-order tests. In I. Olkin et al. (Eds.), Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling (pp. 198–202). Stanford University Press.

Examples

data(d_e, package = "Analitica")
DSCFTest(Sueldo_actual ~ labor, data = d_e)

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