DunnTest {Analitica} | R Documentation |
Dunn's Test for Multiple Comparisons (Non-Parametric)
Description
Performs Dunn's test for pairwise comparisons following a Kruskal-Wallis test. Suitable for non-parametric data (ordinal or non-normal), using rank sums. Includes Holm correction by default for multiple comparisons.
Usage
DunnTest(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: - Simple and widely used non-parametric alternative to Tukey's test. - Handles unequal sample sizes. - Compatible with various p-value corrections (e.g., Holm, Bonferroni).
Disadvantages: - Less powerful than DSCF or Conover when sample sizes vary widely. - Requires ranking all data and can be conservative depending on adjustment.
Value
An object of class "dunn"
and "comparaciones"
, including:
-
Resultados
: Data frame with group comparisons, z-values, raw and adjusted p-values, and significance. -
Promedios
: Mean ranks of each group. -
Orden_Medias
: Group names ordered from highest to lowest rank. -
Metodo
: "Dunn (no paramétrico)".
References
Dunn, O. J. (1964). Multiple comparisons using rank sums. *Technometrics*, 6(3), 241–252. doi:10.1080/00401706.1964.10490181
See Also
Examples
data(d_e, package = "Analitica")
DunnTest(Sueldo_actual ~ labor, data = d_e)