ConoverTest {Analitica} | R Documentation |
Conover-Iman Test for Multiple Comparisons (Non-Parametric)
Description
Performs non-parametric pairwise comparisons based on rank-transformed data using the Conover-Iman procedure. This method is typically applied as a post hoc test following a significant Kruskal-Wallis test to identify specific group differences.
Usage
ConoverTest(formula, data, alpha = 0.05, method.p = "holm")
Arguments
formula |
A formula of the form |
data |
A data frame containing the variables specified in the formula. |
alpha |
Significance level for hypothesis testing (default is 0.05). |
method.p |
Method used to adjust p-values for multiple comparisons (default is |
Details
The Conover-Iman test uses rank-based t-statistics, offering improved statistical power over Dunn's test while maintaining flexibility in sample size.
Advantages: - More powerful than Dunn’s test, especially with moderate group differences. - Robust to non-normal data and suitable for ordinal or skewed distributions. - Allows for unequal sample sizes across groups.
Disadvantages: - Sensitive to heteroscedasticity (non-constant variances). - Requires appropriate p-value adjustment to control the family-wise error rate.
Value
An object of class "conover"
and "comparaciones"
, containing:
-
Resultados
: A data frame with pairwise comparisons, t-statistics, raw and adjusted p-values, and significance markers. -
Promedios
: A named numeric vector with mean ranks for each group. -
Orden_Medias
: A character vector with group names sorted from highest to lowest rank. -
Metodo
: A string describing the method used ("Conover (no parametrico)").
References
Conover, W. J. & Iman, R. L. (1979). "Multiple comparisons using rank sums." Technometrics, 21(4), 489–495.
Examples
data(d_e, package = "Analitica")
ConoverTest(Sueldo_actual ~ labor, data = d_e)