השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| מבחן פוסט-הוק של קונובר-אימן× | מבחן ההשוואה המרובה של דאן× | מבחן Nemenyi Post-Hoc עבור פרידמן× | |
|---|---|---|---|
| תחום | סטטיסטיקה | סטטיסטיקה | סטטיסטיקה |
| משפחה≠ | Regression model | Hypothesis test | Hypothesis test |
| שנת המקור≠ | 1979 | 1964 | 1963 |
| הוגה השיטה≠ | Conover & Iman | Olive Jean Dunn | Peter Nemenyi |
| סוג≠ | Nonparametric post-hoc multiple comparison | Nonparametric pairwise comparison | Nonparametric post-hoc multiple comparison |
| מקור מכונן≠ | Conover, W. J. & Iman, R. L. (1979). On Multiple-Comparisons Procedures. Technical Report LA-7677-MS, Los Alamos Scientific Laboratory. link ↗ | Dunn, O.J. (1964). Multiple Comparisons Using Rank Sums. Technometrics, 6(3), 241–252. DOI ↗ | Nemenyi, P. (1963). Distribution-Free Multiple Comparisons. PhD thesis, Princeton University. link ↗ |
| כינויים | Conover-Iman post-hoc test, Conover post-hoc test, Conover-Iman Post-Hoc Testi | Dunn's post-hoc test, Kruskal-Wallis post-hoc, Dunn Testi — Kruskal-Wallis Post-Hoc | Nemenyi Testi — Friedman Post-Hoc, Nemenyi multiple comparison test, Nemenyi procedure |
| קשורות≠ | 3 | 5 | 5 |
| תקציר≠ | The Conover-Iman test is a rank-based post-hoc procedure, introduced by Conover and Iman in 1979, that identifies which pairs of groups differ after a significant Kruskal-Wallis or Friedman test. It builds a t-style statistic on the pooled ranks and is generally more powerful than the comparable Dunn test. | Dunn's test is a nonparametric post-hoc procedure introduced by Olive Jean Dunn in 1964 to identify which specific pairs of groups differ significantly after a Kruskal-Wallis test has returned a significant overall result. It compares groups pairwise using rank sums and applies a multiple-comparison correction — most commonly Bonferroni or Holm — to control the family-wise error rate. | The Nemenyi test is a nonparametric post-hoc multiple comparison procedure introduced by Peter Nemenyi in his 1963 Princeton doctoral thesis. It is applied after a significant Friedman test to identify which specific pairs of conditions differ from each other in a repeated-measures or blocked design. |
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