Differential Prediction: Understanding a Tool for Detecting Rating Bias in Performance Ratings

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dc.contributor.authorTison, Emilee B.en
dc.contributor.committeechairHauenstein, Neil M. A.en
dc.contributor.committeememberFoti, Roseanne J.en
dc.contributor.committeememberStephens, Robert S.en
dc.contributor.departmentPsychologyen
dc.date.accessioned2014-03-14T20:32:53Zen
dc.date.adate2008-05-05en
dc.date.available2014-03-14T20:32:53Zen
dc.date.issued2008-03-19en
dc.date.rdate2011-01-03en
dc.date.sdate2008-03-26en
dc.description.abstractThree common methods have been used to assess the existence of rating bias in performance ratings: the total association approach, the differential constructs approach and the direct effects approach. One purpose of this study was to examine how the direct effects approach, and more specifically differential prediction analysis, is more useful than the other two approaches in examining the existence of rating bias. However, the usefulness of differential prediction depends on modeling the full rater race X ratee race interaction. Therefore, the second purpose of this study was to examine the conditions where differential prediction has sufficient power to detect this interaction. This was accomplished using monte carlo simulations. Total sample size, magnitude of rating bias, validity of predictor scores, rater race proportion and ratee race proportion were manipulated to identify which conditions of these parameters provided acceptable power to detect the rater race X ratee race interaction; in the conditions where power levels are acceptable, differential prediction is a useful tool in examining the existence of rating bias. The simulation results suggest that total sample size, magnitude of rating bias and rater race proportion have the most impact on power levels. Furthermore, these three parameters interact to effect power. Implications of these results are discussed.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-03262008-102743en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-03262008-102743/en
dc.identifier.urihttp://hdl.handle.net/10919/31549en
dc.publisherVirginia Techen
dc.relation.haspartTisonThesisETD.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectRating Biasen
dc.subjectDifferential Predictionen
dc.subjectPerformance Ratingsen
dc.subjectRace Effectsen
dc.subjectIntercept Biasen
dc.titleDifferential Prediction: Understanding a Tool for Detecting Rating Bias in Performance Ratingsen
dc.typeThesisen
thesis.degree.disciplinePsychologyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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