, Volume 74, Issue 3, pp 531-553

Why Are Experts Correlated? Decomposing Correlations Between Judges

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Abstract

We derive an analytic model of the inter-judge correlation as a function of five underlying parameters. Inter-cue correlation and the number of cues capture our assumptions about the environment, while differentiations between cues, the weights attached to the cues, and (un)reliability describe assumptions about the judges. We study the relative importance of, and interrelations between these five factors with respect to inter-judge correlation. Results highlight the centrality of the inter-cue correlation. We test the model’s predictions with empirical data and illustrate its relevance. For example, we show that, typically, additional judges increase efficacy at a greater rate than additional cues.

This work was supported by the National Science Foundation under Awards SES 02-41434 and 03-45925. The first author was supported by a grant from the National Institutes of Health under Ruth L. Kirschstein National Research Service Award PHS 2 T32 MH014257 (“Quantitative Methods for Behavioral Research”) to the University of Illinois at Urbana-Champaign.