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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 1976
- Accession Number
- ADA026887
Entities
People
- Gary R. Nelson
- Richard V. L. Cooper
Organizations
- RAND Corporation