DSCFTest {Analitica} | R Documentation |
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 |
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)