The analysis of data collected from behavioral assessment instruments is typically conducted using parametric statistics, with little or no reference given to the underlying nature of the scale being used. If the nature of the distances between the scale points is not understood, the concept of normality of the distribution becomes clouded. An empirical approach to studying this problem was developed, using responses to a clinical performance evaluation instrument that uses a four-point behaviorally-anchored scale. Various combinations of nonlinear transformations were applied to the evaluation responses. The factorial structure of the fifteen items constituting the evaluation form was minimally affected by the transformations, suggesting that parametric statistics can be applied to behaviorally-anchored rating scales.