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There are several tests for homogeneity of variances. Fligner and Killeen (1976) suggest ranking (i) the |x_ij - mean| as normal type scores (a) by (0.5 + i/2(N+1)). Where i is the group and j the observation. The replacement of the mean by the median, a modification, is an attempt to improve the robustness of the test. From these scores is formulated a statistic based on a Chi-squared or a F distribution.
According to Conover et al. (1981), the Fligner-Killeen test by median is one of the best tests to use on the basis of robustness and power. Also, by several simulations, the Type I error rate and power is slightly larger when F approximation was used than when the Chi-squared approximation was used. Some of these tests are very sensitive to outliers, but Fligner test is not. Fligner test is the most robust against departures from normality.
Syntax: function FKtest(X,o)
Inputs:
X - Data matrix; Data=column 1, Group=column 2
o - By median=1 (default), mean=2
Outputs:
Complete analysis of the homogeneity of variances test by a Chi-squared and F approximation
Cite As
Antonio Trujillo-Ortiz (2026). FKtest (https://uk.mathworks.com/matlabcentral/fileexchange/25040-fktest), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.2.0.0 (3.13 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
