update

util/evaluation.py

@@ -93,24 +93,24 @@ def statistical_tests(data):
         pair_name_rank = f'{var1}{rank_suffix} vs {var2}{rank_suffix}'
         pair_name_score = f'{var1}{score_suffix} vs {var2}{score_suffix}'
 
-        # Mann-Whitney U Test
-        mw_stat, mw_p = mannwhitneyu(data[f'{var1}{rank_suffix}'], data[f'{var2}{rank_suffix}'])
-        pairwise_results['Mann-Whitney U Test'][pair_name_rank] = {"Statistic": mw_stat, "p-value": mw_p}
-
-        # Wilcoxon Signed-Rank Test
-        if len(data) > 20:
-            wilcoxon_stat, wilcoxon_p = wilcoxon(data[f'{var1}{rank_suffix}'], data[f'{var2}{rank_suffix}'])
-        else:
-            wilcoxon_stat, wilcoxon_p = np.nan, "Sample size too small for Wilcoxon test."
-        pairwise_results['Wilcoxon Test'][pair_name_rank] = {"Statistic": wilcoxon_stat, "p-value": wilcoxon_p}
-
+        # # Mann-Whitney U Test
+        # mw_stat, mw_p = mannwhitneyu(data[f'{var1}{rank_suffix}'], data[f'{var2}{rank_suffix}'])
+        # pairwise_results['Mann-Whitney U Test'][pair_name_rank] = {"Statistic": mw_stat, "p-value": mw_p}
+        #
+        # # Wilcoxon Signed-Rank Test
+        # if len(data) > 20:
+        #     wilcoxon_stat, wilcoxon_p = wilcoxon(data[f'{var1}{rank_suffix}'], data[f'{var2}{rank_suffix}'])
+        # else:
+        #     wilcoxon_stat, wilcoxon_p = np.nan, "Sample size too small for Wilcoxon test."
+        # pairwise_results['Wilcoxon Test'][pair_name_rank] = {"Statistic": wilcoxon_stat, "p-value": wilcoxon_p}
+        #
         # Levene's Test for equality of variances
-        levene_stat, levene_p = levene(data[f'{var1}{score_suffix}'], data[f'{var2}{score_suffix}'])
-        pairwise_results['Levene\'s Test'][pair_name_score] = {"Statistic": levene_stat, "p-value": levene_p}
+        # levene_stat, levene_p = levene(data[f'{var1}{score_suffix}'], data[f'{var2}{score_suffix}'])
+        # pairwise_results['Levene\'s Test'][pair_name_score] = {"Statistic": levene_stat, "p-value": levene_p}
 
         # T-test for independent samples
-        t_stat, t_p = ttest_ind(data[f'{var1}{score_suffix}'], data[f'{var2}{score_suffix}'],
-                                equal_var=(levene_p > 0.05))
+        t_stat, t_p = ttest_ind(data[f'{var1}{score_suffix}'], data[f'{var2}{score_suffix}'])
+                                #equal_var=(levene_p > 0.05))
         pairwise_results['T-Test'][pair_name_score] = {"Statistic": t_stat, "p-value": t_p}
 
     # ANOVA and post-hoc tests if applicable