A New Method for the Statistical Control of Rating Error in Performance Ratings

Bibliographic Data

ID20282934
AuthorsBrendan D Bannister (Human Resources Group Northeastern University, Boston), Angelo J Kinicki (Arizona State University), Angelo S Denisi (University of South Carolina), Peter W Hom (0000-0001-8296-4652, Arizona State University)
Year1987
Volume47
Issue3
Pages583-596
Publication date1987-09-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducational and Psychological Measurement (JOURNAL)
Journal identifiersISSN: 0013-1644 • E-ISSN: 1552-3888
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/001316448704700305
OpenAlexW2090430957
LanguageEN
Citations received2
References cited20

Research on the statistical control of rating error is reviewed. It is shown that current approaches have been criticized on operational grounds. A new approach for statistically controlling rater errors is proposed that avoids problems inherent in past research by using an index of rater error that is theoretically independent of actual performance. Results indicated that partialing out the effects of this extraneous response bias from performance ratings enhanced discriminant validity and slightly attenuated convergent validity (relative to the uncontrolled analysis). In contrast, partialing out overall effectiveness led to substantial reductions in both convergent and discriminant validities

Control (management) · Convergent validity · Discriminant validity · Econometrics · Linear discriminant analysis · Psychometrics · Statistics · Advanced Statistical Methods and Models · Artificial Intelligence · Computer Science · Mathematics · Psychology · Psychometric Methodologies and Testing · Reliability and Agreement in Measurement

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