Estimate ai and average criterion scores for majority and minority groups.

Description

Estimate ai and average criterion scores for majority and minority groups.

Usage

1
aiPux(mr, dx, dy = 1, sr, pct_minority)

Arguments

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.

Value

  • 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

Author(s)

Jeff Jones and Allen Goebl

References

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.

Examples

1
2
aiPux(.6, dx=.8, sr=.3, pct_minority=.25)
aiPux(.6, dx=.8, dy=.2, sr=.3, pct_minority=.25)

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