The Lab
Clintin P. DavisStober
I conduct research within the emerging field of behavioral decisionmaking. My primary research topic is the development and evaluation of mathematical models of individual and group decisionmaking. My recent work examines how individuals integrate multiple pieces of information when making a decision and the rationality of various decision strategies. I am also interested in evaluating the performance of various decision rules in the context of the linear model. Dr. Clintin DavisStober is a Professor of Psychological Sciences at the University of Missouri. He holds a Ph.D. in Quantitative Psychology and an M.S. in Mathematics from the University of Illinois at UrbanaChampaign.
Sanghyuk Park
Hope Synder
Laura Hatz
I am a sixth year graduate student in the clinical area at MU. I graduated from the University of Pittsburgh in 2011 with a BS in psychology and a minor in neuroscience and worked as a research assistant at the Virginia Tech Carilion Research Institute's Addiction Recovery Research Center before enrolling at MU in 2014. My current research focuses on identifying risk factors for alcoholrelated behaviors (e.g., sexual risk taking, driving after drinking), and using mathematical modeling techniques to characterize acute alcohol effects on risky decision making. For my dissertation, I am studying the effects of alcohol intoxication on characteristics of sexual decision making and the application of cognitive process models to common laboratory tasks of impulsivity. My dissertation research is funded by a Ruth L. Kirschstein NRSA fellowship (F31) from the National Institute of Alcohol Abuse and Alcoholism (NIAAA).
Lab Alumni
The Lab
Clintin P. DavisStober
Sanghyuk Park
Hope Synder
Laura Hatz
I am a sixth year graduate student in the clinical area at MU. I graduated from the University of Pittsburgh in 2011 with a BS in psychology and a minor in neuroscience and worked as a research assistant at the Virginia Tech Carilion Research Institute's Addiction Recovery Research Center before enrolling at MU in 2014. My current research focuses on identifying risk factors for alcoholrelated behaviors (e.g., sexual risk taking, driving after drinking), and using mathematical modeling techniques to characterize acute alcohol effects on risky decision making. For my dissertation, I am studying the effects of alcohol intoxication on characteristics of sexual decision making and the application of cognitive process models to common laboratory tasks of impulsivity. My dissertation research is funded by a Ruth L. Kirschstein NRSA fellowship (F31) from the National Institute of Alcohol Abuse and Alcoholism (NIAAA).
Lab Alumni
The Lab
Clintin P. DavisStober
I am a Professor of Psychological Sciences at the University of Missouri. I conduct research within the field of behavioral decisionmaking. My primary research topic is the development and evaluation of mathematical models of individual and group decisionmaking. My recent work examines how individuals integrate multiple pieces of information when making a decision and the rationality of various decision strategies. I am also interested in Bayesian modeling and model selection. I hold a Ph.D. in Quantitative Psychology and an M.S. in Mathematics from the University of Illinois at UrbanaChampaign.
Hope Snyder
My name is Hope Snyder. I am in my fourth year at Mizzou, working towards my PhD in Quantitative Psychology. My research interests are focused on context effects: how surrounding or extra information influences a person's perception and their decisions. I also have an interest in R, an open source statistical software. I enjoy learning and experimenting with all the fancy ways to analyze and visualize data within that environment. Outside of work, I am an avid writer, an average rock climber, and volunteer at the humane society. Everyone needs some kitten/puppy time!
Laura Hatz
I am a sixth year graduate student in the clinical area at MU. I graduated from the University of Pittsburgh in 2011 with a BS in psychology and a minor in neuroscience and worked as a research assistant at the Virginia Tech Carilion Research Institute's Addiction Recovery Research Center before enrolling at MU in 2014. My current research focuses on identifying risk factors for alcoholrelated behaviors (e.g., sexual risk taking, driving after drinking), and using mathematical modeling techniques to characterize acute alcohol effects on risky decision making. For my dissertation, I am studying the effects of alcohol intoxication on characteristics of sexual decision making and the application of cognitive process models to common laboratory tasks of impulsivity. My dissertation research is funded by a Ruth L. Kirschstein NRSA fellowship (F31) from the National Institute of Alcohol Abuse and Alcoholism (NIAAA).
Sanghyuk Park
I am a PhD student in Quantitative Psychology at MU. I obtained my BA in Psychology, and MS in Industrial and Organizational Psychology from Yonsei university, South Korea. I am interested in examining how people make decisions in various contexts through the lens of computational models. One of my recent work is related to evaluating each individualâ€™s decisionmaking pattern with the decision axiom, transitivity, and compare the results between older and younger adults using Bayesian model selection. When I donâ€™t research, I mostly spend time with my family. I am a husband to my beautiful wife, and a father to my lovely 2yearold daughter.
Phillip Hegeman
Phillip Hegeman is a senior undergraduate at the University of Missouri, earning Bachelor of Science degrees in Physics and Mathematics. Although new to the field of quantitative psychology, Phillip is interested in statistical models of belief dynamics as influenced by social circles. In his free time, Phillip enjoys playing the trumpet, most recently competing nationally with the Boston Crusaders Drum and Bugle Corps.
Lab Alumni
Nicholas Brown
Nick currently works at Adobe in San Francisco as a Senior User Experience Researcher. His research interests include injecting psychological models and decision heuristics into the quantitative ML models being developed at Adobe. Nick serves as quantitative experience research expert on the Design team at Adobe, helping designers and product teams understand the user population and create experiences that lead users to success. In his free time he enjoys playing sports, video games and guitar as well as going on outdoor adventures with his wife, Melissa, and dog, Stormwind. Nick completed his Ph.D. in quantitative psychology in 2017.
Simon Segert
Simon is a PhD student in Neuroscience at Princeton University. He is interested in statistical methods and computational modeling of cognitive processes. His work in Clintâ€™s lab centered on the effect of priors in Bayes factor analysis, and the ramifications for model comparisons. Before joining the lab, he obtained an MA in math from UC Berkeley, and a BA in math from Princeton.
Publications
Under review
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Brusco, M., DavisStober, C. P., & Steinley, D. (under review). Ising formulations of some graphtheoretic problems in psychological research: Models and methods.
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Regenwetter, M., DavisStober, C. P., Smeulders, B., Fields, B., & Wang, C. (under review). (Ir)rationality of animal choice? An illustrated guide to testing transitivity.
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In press
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McCarthy, D. M., McCarty, K. N., Hatz, L., Prestigiacomo, C. J., Park, S., & DavisStober, C. P. (in press). Applying Bayesian cognitive models to decisions to drive after drinking. Addiction.
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Kellen, D., DavisStober, C. P., Dunn, J. C., & Kalish, M. L. (in press). The problem of coordination and the pursuit of structural constraints in psychology. Perspectives on Psychological Science.
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Chen, M., Regenwetter, M., & DavisStober, C. P. (in press). Aggregate choice may tell nothing about anyone's individual preferences. Decision Analysis.
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2020
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Hatz, L., Park, S., McCarty, K. N., McCarthy, D. M., & DavisStober, C. P. (2020). Young adults make rational sexual decisions. Psychological Science, 31, 944956.
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Kellen, D., Steiner, M., DavisStober, C. P., & Pappas, N. (2020). Modeling choice paradoxes under risk: From prospect theories to samplingbased accounts. Cognitive Psychology, 118, 101258.
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McCausland, W. J., DavisStober, C. P., Marley, A. A. J., Park, S., & Brown, N. (2020). Testing the random utility hypothesis directly. The Economic Journal, 130, 183207.
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Merkle, E. C., Saw, G., & DavisStober, C. P. (2020). Beating the average forecast: Regularization based on forecaster attributes. Journal of Mathematical Psychology, 98, 102419.
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Motschman, C. A., Warner, O. M., Wycoff, A. M., DavisStober, C. P., & McCarthy, D. M. (2020). Context, acute tolerance, and subjective response affect alcoholimpaired driving decisions. Psychopharmacology, 237, 36033614 .
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Kazmierczak, R. A., DhagatMehta, B., Gulden, E., Lee, L., Ma, L., DavisStober, C. P., Barnett, A. A., & Chabu, Y. C. (2020). Evaluations of CRC2631 toxicity, tumor colonization, and genetic stability in the TRAMP prostate cancer model. Oncotarget, 11, 39433958.
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2019
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DavisStober, C. P., & Regenwetter, M. (2019). The 'paradox' of converging evidence. Psychological Review 126, 865879.
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Park, S., DavisStober, C. P., Synder, H., Messner, W., & Regenwetter, M. (2019). Cognitive aging and tests of rationality. The Spanish Journal of Psychology.
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Brusco, M. J., Steinley, D., Hoffman, M., DavisStober, C. P., & Wasserman, S. W. (2019). On Ising models and algorithms for the construction of symptom networks in psychopathological research. Psychological Methods, 24, 735753.
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Rouder, J. N., Haaf, J. M., DavisStober, C. P., & Hilgard, J. (2019). Beyond overall effects: A Bayesian approach to finding constraints across a collection of studies in metaanalysis. Psychological Methods, 24, 606621.
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Zhao, W. J., DavisStober, C. P., & Bhatia, S. (2019). Optimal cue aggregation in the absence of criterion knowledge. Journal of Behavioral Decision Making, 32, 415430.
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DavisStober, C. P., McCarthy, D., Cavagnaro, D. R., Price, M., Brown, N., & Park, S. (2019). Is cognitive impairment related to violations of rationality? An alcohol intoxication study testing transitivity of preference. Decision, 6, 134144.
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DavisStober, C. P., McCarty, K. N., & McCarthy, D. M. (2019). Risky decision making under alcohol intoxication: Health policy implications. Policy Insights from the Brain and Behavioral Sciences, 6, 6471.
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Segert, S., & DavisStober, C. P. (2019). A general approach to prior adjustment. Journal of Mathematical Psychology, 91, 103118.
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Heck, D. W., & DavisStober, C. P. (2019). Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology, 91, 7087.
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2018
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Cavagnaro, D. R., & DavisStober, C. P. (2018). A modelbased test for treatment effects with probabilistic classifications. Psychological Methods, 23, 672689.
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DavisStober, C. P., Dana, J., & Rouder, J. (2018). Estimation accuracy in the psychological sciences. PLoS ONE, 13, e0207239.
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DavisStober, C. P., Doignon, J.P., Fiorini, S., Glineur, F., & Regenwetter, M. (2018). Extended formulations for order polytopes through network flows. Journal of Mathematical Psychology, 87, 110. *Authors ordered alphabetically.
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Smeulders, B., DavisStober, C. P., Regenwetter, M., & Spieksma, F. C. R. (2018). Testing probabilistic models of choice using column generation. Computers & Operations Research, 95, 3243.
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Regenwetter, M., & DavisStober, C. P. (2018). The role of independence and stationarity in probabilistic models of binary choice. Journal of Behavioral Decision Making, 31, 100114.
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Brown, N., Park, S., Steinley, D., & DavisStober, C. P. (2018). Modeling betweensubject variability in decision strategies via statistical clustering: A pmedian approach. Journal of Behavioral Decision Making, 31, 250264.
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2017
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Kellen, D., Mata, R., & DavisStober, C. P. (2017). Individual classification of strong risk attitudes: An application across lottery types and age groups. Psychonomic Bulletin & Review, 24, 13411349.
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DavisStober, C. P., Brown, N., Park, S., & Regenwetter, M. (2017). Recasting a biologically motivated computational model within a Fechnerian and random utility framework. Journal of Mathematical Psychology, 11, 156164.
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Zhao, J. W., Bhatia, S., & DavisStober, C. P. (2017). Low dimensional representations in multicue judgment. Proceedings of the 39th Annual Meeting of the Cognitive Science Society.
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2016
Marley, A. A. J., DavisStober, C. P., & Steingrimsson, R. (2016). Editors' forward for the special issue in honor of R. Duncan Luce. Journal of Mathematical Psychology, 75, 12.
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DavisStober, C. P., Park, S., Brown, N., & Regenwetter, M. (2016). Reported violations of rationality may be aggregation artifacts. Proceedings of the National Academy of Sciences of the United States of America, 113, E4761E4763.
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Tierney, W., et al. (82 authors). (2016). Data from a prepublication independent replication initiative examining ten moral judgement effects. Scientific Data, 3, article number: 160082.
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DavisStober, C. P., Morey, R. D., Gretton, M., & Heathcote, A. (2016). Bayes factors for statetrace analysis. Journal of Mathematical Psychology, 72, 116129.
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Schweinsburg, M., et al. (81 authors). (2016). The pipeline project: Prepublication independent replications of a single laboratory's research pipeline. Journal of Experimental Social Psychology, 66, 5567.
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Dana, J., & DavisStober, C. P. (2016). Rational foundations for fast and frugal heuristics: An improper linear models approach. Minds and Machines, 26, 6186.
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2015
DavisStober, C. P., Doignon, J.P., & Suck, R. (2015). A note on the eigensystem of the covariance matrix of dichotomous Guttman items. Frontiers in Psychology, 6, 1767.
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DavisStober, C. P., Budescu, D. V., Dana, J., & Broomell, S. B. (2015). The composition of optimally wise crowds. Decision Analysis, 12, 130143.
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Brown, N., DavisStober, C. P., & Regenwetter, M. (2015). From descriptive indices of intransitivity to quantitative assessments: A commentary on Kalenscher et al. (2010). Frontiers in Human Neuroscience, 9, 509.
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DavisStober, C. P., Brown, N., & Cavagnaro, D. R. (2015). Individual differences in the algebraic structure of preference. Journal of Mathematical Psychology, 66, 7082.
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2014
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Cavagnaro, D.R., & DavisStober, C. P. (2014). Transitive in our preferences, but transitive in different ways: An analysis of choice variability. Decision, 1, 102122.
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DavisStober, C. P., Budescu, D. V., Dana, J., & Broomell, S. B. (2014). When is a crowd wise? Decision, 1, 79101.
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DavisStober, C. P., & Dana, J. (2014). Comparing the accuracy of experimental estimates to guessing: A new perspective on replication and the "crisis of confidence" in psychology. Behavior Research Methods, 46, 114. Awarded a Clifford T. Morgan Best Article Award from the Psychonomic Society.
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Regenwetter, M., DavisStober, C. P., Lim, S. H., Guo, Y., Popova, A., Zwilling, C., Cha, Y.C., & Messner, W. (2014). QTEST: Quantitative Testing of theories of binary choice. Decision, 1, 234.
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2013
DavisStober, C. P., & Brown, N. (2013). Evaluating decision maker "type" under padditive utility representations. Journal of Mathematical Psychology, 57, 320328.
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2012
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DavisStober, C. P. (2012). A lexicographic semiorder polytope and probabilistic representations of choice. Journal of Mathematical Psychology, 56, 8694.
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Regenwetter, M., & DavisStober, C. P. (2012). Choice variability versus structural inconsistency of preferences. Psychological Review, 119, 408416.
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2011
DavisStober, C. P., & Brown, N. (2011). A shift in strategy or "error"? Strategy classification over multiple stochastic specifications. Judgment and Decision Making, 6, 800813.
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DavisStober, C. P. (2011). A geometric analysis of when fixed weighting schemes will outperform ordinary least squares. Psychometrika, 76, 650669.
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Regenwetter, M., Dana, J., DavisStober, C. P., & Guo, Y. (2011). Parsimonious testing of transitive or intransitive preferences: Reply to Birnbaum (2011). Psychological Review, 118, 684688.
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Regenwetter, M., Dana, J., & DavisStober, C. P. (2011). Transitivity of preferences. Psychological Review, 118, 4256. Awarded the Exeter Prize for Research in Experimental Economics, Decision Theory and Behavioral Economics.
Regenwetter, M., & DavisStober, C. P. (2011). Ternary paired comparisons induced by semi or interval order preferences. In E. Dzhafarov, L. Perry (Eds.), Descriptive and normative approaches to human behavior. World Scientific.
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2010
DavisStober, C. P. (2010). A bijection between a set of lexicographic semiorders and pairs of noncrossing Dyck paths. Journal of Mathematical Psychology, 54, 471474.
DavisStober, C. P., Dana, J., & Budescu, D. V. (2010). Why recognition is rational: Optimality results on singlevariable decision rules. Judgment and Decision Making, 5, 216229.
DavisStober, C. P., Dana, J., & Budescu, D. V. (2010). A constrained linear estimator for multiple regression. Psychometrika, 75, 521541.
Regenwetter, M., Dana, J., & DavisStober, C. P. (2010). Testing transitivity of preferences on twoalternative forced choice data. Frontiers in Psychology, 1, 148.
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20042009
DavisStober, C. P. (2009). Multinomial models under linear inequality constraints: Applications to measurement theory. Journal of Mathematical Psychology, 53, 113. Awarded the R. Duncan Luce Outstanding Paper Award from the Journal of Mathematical Psychology.
Regenwetter, M., Grofman, B., Popova, A., Messner, W., DavisStober, C. P., & Cavagnaro, D. R. (2009). Behavioral social choice: A status report. Philosophical Transactions of the Royal Society of London B, 364, 833843.
Regenwetter, M., & DavisStober, C. P. (2008). There are many models of transitive preference: A tutorial review and current perspective. In T. Kugler, J. C. Smith, T. Connolly, and Y. J. Son (Eds.), Decision modeling and behavior in uncertain and complex environments. New York: Springer.
DavisStober, C. P. (2008). Review of the book: The mathematics of behavior. Psychometrika, 73, 341.
DavisStober, C. P., Broomell, S., & Lorenz, F. (2006). Review of the book: Exploratory data analysis with Matlab. Psychometrika, 71, 107108.
Rueda, M. R., Posner, M. I., Rothbart, M. K., & DavisStober, C. P. (2004). Development of the time course for processing conflict: An eventrelated potentials study with 4 year olds and adults. BioMed Central Neuroscience, 5, 39.
Software
R package multinomineq (by Daniel Heck)
Implements Gibbs sampling and Bayes factors for multinomial models with linear inequality constraints on the vector of probability parameters. As special cases, the model class includes models that predict a linear order of binomial probabilities (e.g., p[1] < p[2] < p[3] < .50) and mixture models assuming that the parameter vector p must be inside the convex hull of a finite number of predicted patterns (i.e., vertices).
Inequalityconstrained multinomial models have applications in multiple areas in psychology and beyond:

Risky decisions between different gambles to test choice axioms such as transitivity (Regenwetter et al., 2012, 2014).

Outcomebased strategy classification of multiattribute decision strategies such as takethebest (TTB) or weighted additive (WADD; BrÃ¶der & Schiffer, 2003; Heck et al., 2017).

Testing deterministic axioms of measurement and choice (Karabatsos, 2005; Myung et al., 2005).

Fitting and testing nonparametric item response theory models (Karabatsos & Sheu, 2004).

Orderconstrained contingency tables (Klugkist et al., 2007, 2010).

Testing stochastic dominance of response time distributions (Heathcote et al., 2010).

Cognitive diagnostic assessment (Klugkist et al., 2007, 2010).
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A formal definition of inequalityconstrained multinomial models and the implemented computational methods for Bayesian inference is provided in:

Heck, D. W., & DavisStober, C. P. (2019). Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology, 91, 7087.
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Please cite this paper if you use multinomineq in publications.
QTEST
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QTEST is a customdesigned publicdomain statistical analysis package.
The goal of QTEST 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 supercial 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.
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The package and theoretic approach is described in:

Regenwetter, M., DavisStober, C. P., Lim, S. H., Guo, Y., Popova, A., Zwilling, C., Cha, Y.C., & Messner, W. (2014). QTEST: Quantitative Testing of theories of binary choice. Decision, 1, 234.
Please cite this paper if you use QTEST in publications.
Selected Past Talks
Understanding the individual within the crowd: An analysis of how individual forecasters contribute to ideal group forecasts.
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Talk given at the Santa Fe Institute, January 18th, 2019.