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Keywords: Behavioral decision research, order-constrained likelihood-based inference, Luce's challenge, probabilistic specification, theory testing 1 Introduction Behavioral decision researchers in the social and behavioral sciences, who are interested in choice under risk or uncertainty, in intertemporal choice, in probabilistic inference, or many other research areas, invest much effort into proposing, testing, and discussing descriptive theories of pairwise preference.
This article provides the theoretical and conceptual framework underlying a new, general purpose, public-domain tool set, the QT est software. 1 QT est leverages high-level quantitative methodology through mathematical modeling and state-of-the-art, maximum likelihood based, statistics. Yet, it automates enough of the process that many of its features require no more than relatively basic skills in math and statistics.