BrownForsytheTest {Analitica} | R Documentation |
Brown-Forsythe Test for Homogeneity of Variances (Manual Implementation)
Description
Performs the Brown-Forsythe test using absolute deviations from the median of each group, followed by a one-way ANOVA on those deviations.
Usage
BrownForsytheTest(formula, data, alpha = 0.05)
Arguments
formula |
A formula of the form |
data |
A data frame containing the variables. |
alpha |
Significance level (default is 0.05). |
Details
This test is a robust alternative to Bartlett's test, especially useful when the assumption of normality is violated or when outliers are present.
Advantages: - More robust than Bartlett's test under non-normal distributions. - Less sensitive to outliers due to the use of the median.
Disadvantages: - Lower power than Bartlett's test when normality strictly holds. - Assumes that absolute deviations follow similar distributions across groups.
Value
An object of class "homocedasticidad"
, with:
-
Statistic
: F-statistic. -
df1
: Numerator degrees of freedom. -
df2
: Denominator degrees of freedom. -
p_value
: P-value. -
Decision
: "Heterocedastic" or "Homocedastic". -
Method
: "Brown-Forsythe".
References
Brown, M. B., & Forsythe, A. B. (1974). "Robust Tests for the Equality of Variances". Journal of the American Statistical Association, 69(346), 364–367.
Examples
data(d_e, package = "Analitica")
res <- BrownForsytheTest(Sueldo_actual ~ labor, data = d_e)
summary(res)