Skip to main content

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

From: Investigating possible ethnicity and sex bias in clinical examiners: an analysis of data from the MRCP(UK) PACES and nPACES examinations

  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
  1. 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.