Arbitrary metrics in psychology.

Abstract

Many psychological tests have arbitrary metrics but are appropriate for testing psychological theories. Metric arbitrariness is a concern, however, when researchers wish to draw inferences about the true, absolute standing of a group or individual on the latent psychological dimension being measured. The authors illustrate this in the context of 2 case studies in which psychologists need to develop inventories with nonarbitrary metrics. One example comes from social psychology, where researchers have begun using the Implicit Association Test to provide the lay public with feedback about their "hidden biases" via popular Internet Web pages. The other example comes from clinical psychology, where researchers often wish to evaluate the real-world importance of interventions. As the authors show, both pursuits require researchers to conduct formal research that makes their metrics nonarbitrary by linking test scores to meaningful real-world events.