Measuring the Impact of Judge Severity on Examination Scores

Abstract

Abstract In order to obtain objective measurement for examinations that are graded by judges, an extension of the Rasch model designed to analyze examinations with more than two facets (items/examinees) is used. This extended Rasch model calibrates the elements of each facet of the examination (i.e., examinee performances, items, and judges) on a common log-linear scale. A network for assigning judges to examinations is used to link all facets. Real examination data from the "clinical assessment" part of a certification examination are used to illustrate the application. A range of item difficulties and judge severities were found. Comparison of examinee raw scores with objective linear measures corrected for variations in judge severity shows that judge severity can have a substantial impact on a raw score. Correcting for judge severity improves the fairness of examinee measures and of the subsequent pass-fail decisions because the uncorrected raw scores favor examinee performances graded by lenient judges.