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

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

Dwass-Steel-Critchlow-Fligner (DSCF) Test (Non-Parametric) v2.0.3

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",
  na.rm = TRUE,
  include_kw = TRUE
)

Arguments

formula	y ~ group
data	data.frame con las variables
alpha	nivel (0.05 por defecto) just for the little star
method.p	adjustment method (default "holm")
na.rm	remove NA (TRUE by default)
include_kw	if TRUE, add summary of Kruskal-Wallis test

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. - It is only useful in completely random or single-factor designs.

Value

objeto con clases c("comparaciones","dscf")

References

Dwass, M. (1960). Some k-sample rank-order tests. In I. Olkin et al. (Eds.), Contribution1s 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 Dec. 3, 2025, 9:07 a.m.