Decision Making and Data Science

We study how individuals make risky choices and whether they do so in consistent, predictable ways that reveal their motivations and goals.   We use the language of mathematics and statistical modeling to make these concepts precise and testable.   In collaboration with other labs, we seek to better understand decision making across many experimental and observational settings, with a particular focus on risky decisions involving alcohol and addictions.  

In tandem with our empirical investigations, we develop and apply advanced quantitative methods to make sound statistical inferences and predictions.   This scope of work includes Bayesian cognitive modeling, order-constrained statistical inference, network modeling, and machine learning.

The lab has received funding from the National Institutes for Health and the National Science Foundation.  We support transparency in science and make our data, code, and related materials publicly available on established file sharing websites.

Recent news stories featuring lab members

https://www.psychologytoday.com/us/blog/the-right-mindset/202010/safe-sex-or-risky-romance

https://www.voxmagazine.com/news/crisis-fatigue-in-2020/article_29f132ae-134a-11eb-a421-6f31482c4ef1.html

Recent Blog Posts

The Lab

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Clintin P. Davis-Stober

I conduct research within the emerging field of behavioral decision-making. My primary research topic is the development and evaluation of mathematical models of individual and group decision-making. 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 Davis-Stober 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 Urbana-Champaign.

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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 alcohol-related 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).

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Lab Alumni

The Lab

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Clintin P. Davis-Stober
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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 alcohol-related 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

 
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Clintin P. Davis-Stober

I am a Professor of Psychological Sciences at the University of Missouri. I conduct research within the field of behavioral decision-making. My primary research topic is the development and evaluation of mathematical models of individual and group decision-making. 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 Urbana-Champaign.  

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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!

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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 alcohol-related 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).

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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 individual’s decision-making pattern with the decision axiom, transitivity, and compare the results between older and younger adults using Bayesian model selection. When I don’t research, I mostly spend time with my family. I am a husband to my beautiful wife, and a father to my lovely 2-year-old daughter. 

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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

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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.

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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 Clint’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. 

The Lab

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Clintin P. Davis-Stober, Ph.D.

Dr. Davis-Stober is a Professor of Psychological Sciences and a Core Faculty member of the Institute for Data Science and Informatics 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 Urbana-Champaign. He is the recipient of multiple best paper awards for peer-reviewed publications, including the Exeter Prize.  Dr. Davis-Stober is also a recipient of the William K. Estes Early Career award from the Society for Mathematical Psychology. Dr. Davis-Stober is an Associate Editor at Journal of Mathematical Psychology and British Journal for Mathematical and Statistical Psychology.  He is a fellow of the Psychonomic Society. 

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Sara McMullin, Ph.D

I am a first year postdoctoral research fellow funded on the NIAAA T32 institutional training grant. I earned a BA in psychology and a minor in biology from Webster University in 2014 and a PhD in experimental psychology with concentrations in cognitive neuroscience and quantitative methodology in 2020. My research focuses on how stress influences decision making in addiction populations across the lifespan. Specifically, I investigate how lab-based acute stress and lifetime stress influences decision making strategy use and choices. Further, I apply these methods in assessing alcohol-related decision making regarding excessive alcohol consumption and alcohol-impaired driving. I approach research using models from clinical science, cognitive neuroscience, and lifespan psychology by integrating self-report, behavioral, cognitive, and physiological methods.

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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_headshot4_crop.jpg
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 alcohol-related 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_Olivia_edited.jpg
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 individual’s decision-making pattern with the decision axiom, transitivity, and compare the results between older and younger adults using Bayesian model selection. When I don’t research, I mostly spend time with my family. I am a husband to my beautiful wife, and a father to my lovely 2-year-old daughter. 

Hegeman Headshot_edited.jpg
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

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Nicholas Brown, Ph.D.

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.

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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 Clint’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

Singmann, H., Kellen, D., Cox, G. E., Chandramouli, S. H., Davis-Stober, C. P., Dunn, J. C., Gronau, Q. F., Kalish, M. L., McMullin, S. D., Navarro, D. J., & Shiffrin, R. M. (under review). Statistics in the service of science: Don't let the tail wag the dog. doi.org/10.31234/osf.io/kxhfu

In press

McMullin, S. D., Motschman, C., Hatz, L., McCarthy, D., & Davis-Stober, C. P. (in press). Decision strategies while intoxicated relate to alcohol-impaired driving attitudes and intentions. Psychology of Addictive Behaviors.  doi.org/10.31234/osf.io/7tmuh

2021

McCarthy, D. M., McCarty, K. N., Hatz, L., Prestigiacomo, C. J., Park, S., & Davis-Stober, C. P. (2021). Applying Bayesian cognitive models to decisions to drive after drinking. Addiction, 116, 1424-1430. doi.org/10.1111/add.15302

Kellen, D., Davis-Stober, C. P., Dunn, J. C., & Kalish, M. L. (2021). The problem of coordination and the pursuit of structural constraints in psychology. Perspectives on Psychological Science, 16, 767-778. 10.31234/osf.io/3eupv

Chen, M., Regenwetter, M., & Davis-Stober, C. P. (2021). Collective choice may tell nothing about anyone's individual preferences. Decision Analysis, 18, 1-24. doi.org/10.1287/deca.2020.0417

Brusco, M., Davis-Stober, C. P., & Steinley, D. (2021). Ising formulations of some graph-theoretic problems in psychological research: Models and methods. Journal of Mathematical Psychology, 102, 10253610.31234/osf.io/4udfw

Regenwetter, M., Davis-Stober, C. P.,  Smeulders, B., Fields, B., & Wang, C. (2021). (Ir)rationality of animal choice? A guide to testing transitivity. The Quarterly Review of Biology, 96, 169-204.

2020

Hatz, L., Park, S., McCarty, K. N., McCarthy, D. M., & Davis-Stober, C. P. (2020). Young adults make rational sexual decisions. Psychological Science, 31, 944-956. doi.org/10.1177/0956797620925036

Kellen, D., Steiner, M., Davis-Stober, C. P., & Pappas, N. (2020). Modeling choice paradoxes under risk: From prospect theories to sampling-based accounts. Cognitive Psychology, 118, 101258. doi.org/10.1016/j.cogpsych.2019.101258

McCausland, W. J., Davis-Stober, C. P., Marley, A. A. J., Park, S., & Brown, N. (2020). Testing the random utility hypothesis directly. The Economic Journal, 130, 183-207. doi.org/10.1093/ej/uez039

Merkle, E. C., Saw, G., & Davis-Stober, C. P. (2020). Beating the average forecast: Regularization based on forecaster attributes. Journal of Mathematical Psychology, 98, 102419. doi.org/10.1016/j.jmp.2020.102419

Motschman, C. A., Warner, O. M., Wycoff, A. M., Davis-Stober, C. P., & McCarthy, D. M. (2020). Context, acute tolerance, and subjective response affect alcohol-impaired driving decisions. Psychopharmacology, 237, 3603-3614. doi.org/10.1007/s00213-020-05639-0

Kazmierczak, R. A., Dhagat-Mehta, B., Gulden, E., Lee, L., Ma, L., Davis-Stober, 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, 3943-3958. 10.18632/oncotarget.27769

2019

Davis-Stober, C. P., & Regenwetter, M. (2019). The 'paradox' of converging evidence. Psychological Review, 126, 865-879. doi.org/10.1037/rev0000156

Park, S., Davis-Stober, C. P., Synder, H., Messner, W., & Regenwetter, M. (2019). Cognitive aging and tests of rationality. The Spanish Journal of Psychology. doi.org/10.1017/sjp.2019.52

Brusco, M. J., Steinley, D., Hoffman, M., Davis-Stober, C. P., & Wasserman, S. W. (2019). On Ising models and algorithms for the construction of symptom networks in psychopathological research. Psychological Methods, 24, 735-753. doi.org/10.1037/met0000207

Rouder, J. N., Haaf, J. M., Davis-Stober, C. P., & Hilgard, J. (2019). Beyond overall effects: A Bayesian approach to finding constraints across a collection of studies in meta-analysis. Psychological Methods, 24, 606-621. doi.org/10.1037/met0000216

Zhao, W. J., Davis-Stober, C. P., & Bhatia, S. (2019). Optimal cue aggregation in the absence of criterion knowledge. Journal of Behavioral Decision Making, 32, 415-430. doi.org/10.1002/bdm.2123

Davis-Stober, 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, 134-144. doi.org/10.1037/dec0000093

Davis-Stober, 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, 64-71. doi.org/10.1177/2372732218818587

Segert, S., & Davis-Stober, C. P. (2019). A general approach to prior adjustment. Journal of Mathematical Psychology, 91, 103-118. doi.org/10.1016/j.jmp.2019.04.002

Heck, D. W., & Davis-Stober, C. P. (2019). Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology, 91, 70-87. doi.org/10.1016/j.jmp.2019.03.004

2018

Cavagnaro, D. R., & Davis-Stober, C. P. (2018). A model-based test for treatment effects with probabilistic classifications. Psychological Methods, 23, 672-689. doi.org/10.1037/met0000173

Davis-Stober, C. P., Dana, J., & Rouder, J. (2018). Estimation accuracy in the psychological sciences. PLoS ONE, 13, e0207239. 

doi.org/10.1371/journal.pone.0207239

Davis-Stober, 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, 1-10. *Authors ordered alphabetically. doi.org/10.1016/j.jmp.2018.08.003

Smeulders, B., Davis-Stober, C. P., Regenwetter, M., & Spieksma, F. C. R. (2018). Testing probabilistic models of choice using column generation. Computers & Operations Research, 95, 32-43. doi.org/10.1016/j.cor.2018.03.001

Regenwetter, M., & Davis-Stober, C. P. (2018). The role of independence and stationarity in probabilistic models of binary choice. Journal of Behavioral Decision Making, 31, 100-114. doi.org/10.1002/bdm.2037

Brown, N., Park, S., Steinley, D., & Davis-Stober, C. P. (2018). Modeling between-subject variability in decision strategies via statistical clustering: A p-median approach. Journal of Behavioral Decision Making, 31, 250-264. doi.org/10.1002/bdm.1957

2017

Kellen, D., Mata, R., & Davis-Stober, C. P. (2017). Individual classification of strong risk attitudes: An application across lottery types and age groups. Psychonomic Bulletin & Review, 24, 1341-1349. doi.org/10.3758/s13423-016-1212-5

Davis-Stober, 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, 156-164. doi.org/10.1016/j.jmp.2016.10.009

Zhao, J. W., Bhatia, S., & Davis-Stober, C. P. (2017). Low dimensional representations in multi-cue judgment. Proceedings of the 39th Annual Meeting of the Cognitive Science Society.

2016

Davis-Stober, 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, E4761-E4763. doi.org/10.1073/pnas.1606997113

Marley, A. A. J., Davis-Stober, C. P., & Steingrimsson, R. (2016). Editors' forward for the special issue in honor of R. Duncan Luce. Journal of Mathematical Psychology, 75, 1-2.

Tierney, W., et al. (82 authors). (2016). Data from a pre-publication independent replication initiative examining ten moral judgement effects. Scientific Data, 3, article number: 160082. doi.org/10.1038/sdata.2016.82

Davis-Stober, C. P., Morey, R. D., Gretton, M., & Heathcote, A. (2016). Bayes factors for state-trace analysis. Journal of Mathematical Psychology, 72, 116-129. doi.org/10.1016/j.jmp.2015.08.004

Schweinsburg, M., et al. (81 authors). (2016). The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline. Journal of Experimental Social Psychology, 66, 55-67. doi.org/10.1016/j.jesp.2015.10.001

Dana, J., & Davis-Stober, C. P. (2016). Rational foundations for fast and frugal heuristics: An improper linear models approach. Minds and Machines, 26, 61-86. doi.org/10.1007/s11023-015-9372-z

2015

 

Davis-Stober, 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. doi.org/10.3389/fpsyg.2015.01767

Davis-Stober, C. P., Budescu, D. V., Dana, J., & Broomell, S. B. (2015). The composition of optimally wise crowds. Decision Analysis, 12, 130-143. doi.org/10.1287/deca.2015.0315

Brown, N., Davis-Stober, 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. doi.org/10.3389/fnhum.2015.00509

Davis-Stober, C. P., Brown, N., & Cavagnaro, D. R. (2015). Individual differences in the algebraic structure of preference. Journal of Mathematical Psychology, 66, 70-82. doi.org/10.1016/j.jmp.2014.12.003

2014

Cavagnaro, D.R., & Davis-Stober, C. P. (2014). Transitive in our preferences, but transitive in different ways: An analysis of choice variability. Decision, 1, 102-122. doi.org/10.1037/dec0000011

Davis-Stober, C. P., Budescu, D. V., Dana, J., & Broomell, S. B. (2014). When is a crowd wise? Decision, 1, 79-101. doi.org/10.1037/dec0000004

Davis-Stober, 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, 1-14Awarded a Clifford T. Morgan Best Article Award from the Psychonomic Society. doi.org/10.3758/s13428-013-0342-1

Regenwetter, M., Davis-Stober, 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, 2-34. doi.org/10.1037/dec0000007

2013

 

Davis-Stober, C. P., & Brown, N. (2013). Evaluating decision maker "type" under p-additive utility representations. Journal of Mathematical Psychology, 57, 320-328. doi.org/10.1016/j.jmp.2013.08.002

2012

Davis-Stober, C. P. (2012). A lexicographic semiorder polytope and probabilistic representations of choice. Journal of Mathematical Psychology, 56, 86-94. doi.org/10.1016/j.jmp.2012.01.003

Regenwetter, M., & Davis-Stober, C. P. (2012). Choice variability versus structural inconsistency of preferences. Psychological Review, 119, 408-416. doi.org/10.1037/a0027372

2011

 

Davis-Stober, C. P., & Brown, N. (2011). A shift in strategy or "error"? Strategy classification over multiple stochastic specifications. Judgment and Decision Making, 6, 800-813.

Davis-Stober, C. P. (2011). A geometric analysis of when fixed weighting schemes will outperform ordinary least squares. Psychometrika, 76, 650-669. doi.org/10.1007/s11336-011-9229-1

Regenwetter, M., Dana, J., Davis-Stober, C. P., & Guo, Y. (2011). Parsimonious testing of transitive or intransitive preferences: Reply to Birnbaum (2011). Psychological Review, 118, 684-688. doi.org/10.1037/a0025291

Regenwetter, M., Dana, J., & Davis-Stober, C. P. (2011). Transitivity of preferences. Psychological Review, 118, 42-56. Awarded the Exeter Prize for Research in Experimental Economics, Decision Theory and Behavioral Economics. doi.org/10.1037/a0021150

 

Regenwetter, M., & Davis-Stober, 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.

2010

 

Davis-Stober, C. P. (2010). A bijection between a set of lexicographic semiorders and pairs of non-crossing Dyck paths. Journal of Mathematical Psychology, 54, 471-474. doi.org/10.1016/j.jmp.2010.09.001

 

Davis-Stober, C. P., Dana, J., & Budescu, D. V. (2010). Why recognition is rational: Optimality results on single-variable decision rules. Judgment and Decision Making, 5, 216-229.

 

Davis-Stober, C. P., Dana, J., & Budescu, D. V. (2010). A constrained linear estimator for multiple regression. Psychometrika, 75, 521-541. doi.org/10.1007/s11336-010-9162-8

 

Regenwetter, M., Dana, J., & Davis-Stober, C. P. (2010). Testing transitivity of preferences on two-alternative forced choice data. Frontiers in Psychology, 1, 148. doi.org/10.3389/fpsyg.2010.00148

2004-2009

 

Davis-Stober, C. P. (2009). Multinomial models under linear inequality constraints: Applications to measurement theory. Journal of Mathematical Psychology, 53, 1-13. Awarded the R. Duncan Luce Outstanding Paper Award from the Journal of Mathematical Psychology. doi.org/10.1016/j.jmp.2008.08.003

 

Regenwetter, M., Grofman, B., Popova, A., Messner, W., Davis-Stober, C. P., & Cavagnaro, D. R. (2009). Behavioral social choice: A status report. Philosophical Transactions of the Royal Society of London B, 364, 833-843. doi.org/10.1098/rstb.2008.0259

 

Regenwetter, M., & Davis-Stober, 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.

 

Davis-Stober, C. P. (2008). Review of the book: The mathematics of behavior. Psychometrika, 73, 341.

 

Davis-Stober, C. P., Broomell, S., & Lorenz, F. (2006). Review of the book: Exploratory data analysis with Matlab. Psychometrika, 71, 107-108.

 

Rueda, M. R., Posner, M. I., Rothbart, M. K., & Davis-Stober, C. P. (2004). Development of the time course for processing conflict: An event-related potentials study with 4 year olds and adults. BioMed Central Neuroscience, 5, 39. doi.org/10.1186/1471-2202-5-39

 

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).

Inequality-constrained 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).

  • Outcome-based strategy classification of multiattribute decision strategies such as take-the-best (TTB) or weighted additive (WADD; Bröder & 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).

  • Order-constrained 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).

A formal definition of inequality-constrained multinomial models and the implemented computational methods for Bayesian inference is provided in:

  • Heck, D. W., & Davis-Stober, C. P. (2019). Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology, 91, 70-87.

Please cite this paper if you use multinomineq in publications.

QTEST 

QTEST is a custom-designed public-domain 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 super cial 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 package and theoretic approach is described in:

  • Regenwetter, M., Davis-Stober, 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, 2-34.

 

Please cite this paper if you use QTEST in publications.

 
 

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stoberc@missouri.edu | twitter: @ClintinS 

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