Description Usage Arguments Value Author(s) References Examples
Estimate ai and average criterion scores for majority and minority groups.
1 | aiPux(mr, dx, dy = 1, sr, pct_minority)
|
mr |
The correlation between the predictor and criterion composites. |
dx |
A vector of d values for the predictors. These d values are expected to have been computed in the direction of Majority - Minority. |
dy |
A vector of d values for the criteria These d values are expected to have been computed in the direction of Majority - Minority. |
sr |
The percentage of the applicant population who are selected. |
pct_minority |
The percentage of the applicant population who are part of a given minority group. |
AIAdverse Impact
Overeall_srThe overall selection ratio set by the user
Majority_srMajority Selection Rate
Minority_srMinority Selection Rate
Majority_StandardizedPredicted composite criterion score relative to the majority population
Global_StandardizedPredicted composite criterion score relative to the overall population
Jeff Jones and Allen Goebl
De Corte, W., Lievens, F.(2003). A Practical procedure to estimate the quality and the adverse impact of single-stage selection decisions. International Journal of Selection and Assessment., 11(1), 87-95.
1 2 |
$AI
[1] 0.3420737
$Overall_sr
[1] 0.3
$Majority_sr
[1] 0.3590524
$Minority_sr
[1] 0.1228224
$Majority_Standardized
[,1]
Zi -0.006678063
Za 0.624605487
Zt 0.559981664
$Global_Standardized
[,1]
Zi 0.2232875
Za 0.8025930
Zt 0.7432902
$AI
[1] 0.3420737
$Overall_sr
[1] 0.3
$Majority_sr
[1] 0.3590524
$Minority_sr
[1] 0.1228224
$Majority_Standardized
[,1]
Zi 0.7933219
Za 0.6246055
Zt 0.6418633
$Global_Standardized
[,1]
Zi 0.8401772
Za 0.6720899
Zt 0.6892833
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