Analitica (version 2.2.0)

DSCFTest: 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
)

Value

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

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.

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)