BayesSDT: Software for Bayesian inference with signal detection theory |
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Authors: | Michael D. Lee |
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Affiliation: | Department of Cognitive Sciences, University of California, Irvine, California 92697-5100, USA. mdlee@uci.edu |
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Abstract: | This article describes and demonstrates the BayesSDT MATLAB-based software package for performing Bayesian analysis with equal-variance Gaussian signal detection theory (SDT). The software uses WinBUGS to draw samples from the posterior distribution of six SDT parameters: discriminability, hit rate, false alarm rate, criterion, and two alternative measures of bias. The software either provides a simple MATLAB graphical user interface or allows a more general MATLAB function call to produce graphs of the posterior distribution for each parameter of interest for each data set, as well as to return the full set of posteriorsamples. |
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