Table 1.
The table shows separately for analyses of hawk-dove differences, male–female differences, White-nonWhite differences, and differences between odd and even numbered candidates (see columns), the numbers of examiners who reached statistical significance (rows) on various criteria
| |
Hawk-Dove |
Male–female |
White-NonWhite |
Odd-Even numbering |
||||
|---|---|---|---|---|---|---|---|---|
| |
Positive: Examiner hawkish |
Positive: Males score higher than females |
Positive: Whites score higher than non-Whites |
|
|
|||
| PACES | nPACES | PACES | nPACES | PACES | nPACES | PACES | nPACES | |
| Negative effect: P < .05 corrected |
34 (1.9%) |
35 (2.3%) |
0 |
0 |
2 (0.1%) |
1 (0.1%) |
0 |
0 |
| Negative effect: P < .05 uncorrected (chance expectation = 2.5%) |
198 (11.1%) |
235 (15.7%) |
73 (4.1%) |
63 (4.2%) |
73 (4.4%) |
48 (3.6%) |
60 (3.2%) |
51 (3.2%) |
| Not significant (uncorrected, p > .05) |
1339 (74.8%) |
989 (66.0%) |
1638 (91.5%) |
1379 (92.1%) |
1491 (90.4%) |
1229 (92.2%) |
1680 (93.9%) |
1396 (93.2%) |
| Positive effect: P < .05 uncorrected (chance expectation = 2.5%) |
192 (10.7%) |
200 (13.4%) |
79 (4.4%) |
55 (3.7%) |
82 (5.0%) |
55 (4.1%) |
50 (3.0%) |
51 (3.6%) |
| Positive effect: P < .05 corrected |
27 (1.5%) |
39 (2.6%) |
0 |
0 |
1 (0.1%) |
0 |
0 |
0 |
| N examiners | 1790 | 1498 | 1790 | 1497 | 1649 | 1333 | 1790 | 1498 |
Levels of statistical significance are divided into five groups, those who are significant at a Bonferroni corrected level of p < .05 (first and fifth rows), those who are significant at a non-Bonferroni-corrected level of p < .05 (second and fourth rows), and those who are not significant at a non-Bonferroni-corrected level of p < .05 (middle row). ‘Positive’ refers., arbitrarily, to examiners being more hawkish (i.e. giving lower overall scores), giving higher scores to male candidates, giving higher scores to White candidates, or giving higher scores to odd-numbered candidates. By chance alone one would expect 95% of candidates to be in the ‘non-significant’ group, with the remaining 5% of candidates distributed evenly between negative and positive effects.