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- aggregation classification "A1".
- aggregation creator B290948.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2010".
- aggregation format "application/pdf".
- aggregation hasFormat 1232343.bibtex.
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- aggregation isPartOf urn:issn:0965-075X.
- aggregation language "eng".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Social Sciences".
- aggregation title "Selecting predictor subsets: considering validity and adverse impact".
- aggregation abstract "The paper proposes a procedure for designing Pareto-optimal selection systems considering validity, adverse impact and constraints on the number of predictors from a larger subset that can be included in an operational selection system. The procedure determines Pareto-optimal composites of a given maximum size thereby solving the dual task of identifying the predictors that will be included in the reduced set and determining the weights with which the retained predictors will be combined to the composite predictor. Compared with earlier proposals, the simultaneous consideration of both tasks makes it possible to combine several strategies for reducing adverse impact in a single procedure. In particular, the present approach allows integrating (a) investigating a large number of possible predictors (such as multitest battery of ability tests, or a collection of ability and nonability measures); (b) explicit predictor weighting within feasible test procedures of a given limited size.".
- aggregation authorList BK574682.
- aggregation endPage "270".
- aggregation issue "3".
- aggregation startPage "260".
- aggregation volume "18".
- aggregation aggregates 1232525.
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