FKTest {Analitica} | R Documentation |
Fligner-Killeen Test for Homogeneity of Variances (Manual Implementation)
Description
Performs a non-parametric Fligner-Killeen test for equality of variances across two or more groups, using raw vectors via a formula interface.
Usage
FKTest(formula, data, alpha = 0.05)
Arguments
formula |
A formula of the form |
data |
A data frame containing the variables in the formula. |
alpha |
Significance level (default is 0.05). |
Details
This test is particularly useful when the assumption of normality is violated, as it is robust to outliers and distributional deviations. It serves as a reliable alternative to Bartlett’s test when data do not follow a normal distribution.
Advantages: - Non-parametric: No assumption of normality. - Robust to outliers. - Suitable for heterogeneous sample sizes.
Disadvantages: - Less powerful than parametric tests under normality. - May be computationally intensive with large datasets.
Value
An object of class "homocedasticidad"
, containing:
- Statistic
The Fligner-Killeen chi-squared statistic.
- df
Degrees of freedom.
- p_value
The p-value for the test.
- Decision
"Homoscedastic"
or"Heteroscedastic"
depending on the test result.- Method
A string indicating the method used ("Fligner-Killeen").
References
Fligner, M. A., & Killeen, T. J. (1976). "Distribution-free two-sample tests for scale." Journal of the American Statistical Association, 71(353), 210–213. <https://doi.org/10.1080/01621459.1976.10480351>
Examples
data(d_e, package = "Analitica")
res <- FKTest(Sueldo_actual ~ labor, data = d_e)
summary(res)