Analytic Methods for Adjusting Subjective Rating Schemes.

Abstract : Subjective evaluations of individual performances by supervisors are subject to bias. This report develops statistical and econometric techniques for correcting biases in models of individual performance using a variant of the Classical linear regression model. A multi-scale model is proposed to deal with two types of bias: location bias when an individual's performance is systematically overestimated or underestimated, and scale bias when differences among individuals rated are exaggerated or minimized. Several specific multi- scale estimating techniques are developed, and multi-scale estimators are applied to the problem of estimating the cost of on-the-job training in the military.