Optimal Cutting Scores Using A Linear Loss Function

Abstract

The situation is considered in which a total score on a test is used for classifying examinees into two categories: "accepted (with scores above a cutting score on the test) and "not accepted" (with scores below the cutting score). A value on the latent variable is fixed in advance; examinees above this value are "suitable" and those below are "not suit able." Using a linear loss function, a procedure is described for computing a cutting score that mini mizes the risk for the decision rule. The procedure is demonstrated with a criterion-referenced achieve ment test of elementary statistics administered to 167 students.