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 y ~ group, where y is a numeric variable and group is a factor indicating group membership.

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 "holm").

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:

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)



[Package Analitica version 1.8.5 Index]