WilcoxonSRTest

StatisticalTest

DashAI.back.statistical_tests.WilcoxonSRTest

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Non-parametric alternative to the paired t-test for related samples.

This implementation uses the Wilcoxon signed-rank test on the paired score differences between two models evaluated on the same folds. It is suitable when the paired differences are not approximately normal and is commonly used as a robust alternative to the paired t-test.

References

• https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.wilcoxon.html
• Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics Bulletin, 1(6), 80-83.

Methods

get_metadata(cls) -> dict

Defined on WilcoxonSRTest

Return UI metadata describing the test capabilities and interpretation.

run(self, scores: dict[str, list[float]], alpha: float = 0.05, alternative: str = 'two-sided', correction_method: str = None, **kwargs) -> DashAI.back.statistical_tests.statistical_test_result.StatisticalTestResult

Defined on WilcoxonSRTest

Run the Wilcoxon signed-rank test on paired score differences.

Parameters

scores : dict[str, list[float]]

Mapping from model/run names to paired score vectors.

alpha : float, optional

Significance level used to decide whether the null hypothesis is rejected, by default 0.05.

alternative : str, optional

Direction of the alternative hypothesis: two-sided, greater, or less.

correction_method : str or None, optional

Method used to adjust p-values when more than two models are being compared.

Returns

StatisticalTestResult

A result object with the signed-rank statistic, p-value, and the significance decision.