A Hierarchical Unequal-Variance Signal Detection Model for Binary Responses

Gaussian signal detection models with equal variance are commonly used in simple yes-no detection and discrimination experiments whereas more flexible models with unequal variance require additional information. Here, a hierarchical Bayesian model with equal-variance is extended to an unequal-variance model so that it is applicable to binary responses from a random sample of participants. This unequal-variance model is investigated analytically, in simulations and three applications using existing data sets. The results suggest that parameters of this model are accurate and reliable, providing a promising alternative to the ubiquitous equal-variance model.