The uniform distribution in signal detection theory

TLDR: In this article, the robustness of signal detection theory (SDT) is investigated with respect to the form of the underlying distributions, and it is shown that the SDT model with uniform distributions yields non-significant goodness-of-fit statistics for many sets of data.

Abstract: The robustness of signal detection theory (SDT) is investigated with respect to the form of the underlying distributions. Usually these distributions are taken to be normal; here an SDT model based on two overlapping uniform (rectangular) distributions is examined, for the Yes/No experiment and the rating-method experiment. In the Yes/No case the SDT measure (using uniform distributions) is found to be equivalent to a measure recently proposed by Hammerton & Altham (1971), and, from contingency-table considerations, it is a measure likely to give similar conclusions to the SDT measure using normal distributions. In the rating-method case it is surprising to find that the SDT model with uniform distributions yields non-significant goodness-of-fit statistics for many sets of data.