Type I error rates and power analyses for single-point sensitivity measures

Abstract

Experiments often produce a hit rate and a false alarm rate in each of two conditions. These response rates are summarized into a single-point sensitivity measure such as d′, and t tests are conducted to test for experimental effects. Using large-scale Monte Carlo simulations, we evaluate the Type I error rates and power that result from four commonly used single-point measures: d′, A′, percent correct, and γ. We also test a newly proposed measure called γc. For all measures, we consider several ways of handling cases in which false alarm rate = 0 or hit rate = 1. The results of our simulations indicate that power is similar for these measures but that the Type I error rates are often unacceptably high. Type I errors are minimized when the selected sensitivity measure is theoretically appropriate for the data. Copyright 2008 Psychonomic Society, Inc.