title: QTest: Quantitative Testing of Theories of Binary Choice.
abstract: The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. 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. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of "Random Cumulative Prospect Theory." A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.
authors.affiliation: Department of Psychology, University of Illinois at Urbana-Champaign, USA.
authors.forename: Michel
authors.initials: M
authors.lastname: Regenwetter
authors.affiliation: Department of Psychology, University of Missouri at Columbia, USA.
authors.forename: Clintin P
authors.initials: CP
authors.lastname: Davis-Stober
authors.affiliation: Department of Mechanical Engineering, National University of Singapore, Singapore.
authors.forename: Shiau Hong
authors.initials: SH
authors.lastname: Lim
authors.affiliation: Korea Institute of Public Finance, Korea.
authors.forename: Ying
authors.initials: Y
authors.lastname: Guo
authors.affiliation: State Farm Insurance, USA.
authors.forename: Anna
authors.initials: A
authors.lastname: Popova
authors.forename: Chris
authors.initials: C
authors.lastname: Zwilling
authors.forename: Yun-Shil
authors.initials: YS
authors.lastname: Cha
authors.forename: William
authors.initials: W
authors.lastname: Messner
keywords: Behavioral decision research; Luce's challenge; order-constrained likelihood-based inference; probabilistic specification; theory testing