![]() The paper is supplemented with a custom-designed public-domain statistical analysis package, the QT est software. ![]() ![]() Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions.
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