activity
20142025
most citedMultinomial Models with Linear Inequality Constraints: Overview and Improvements of Computational Methods for Bayesian Inference

38 citations · 38 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Benchmarking the rationality of AI decision making using the transitivity axiom

Kiwon Song, James M. Jennings, Clintin P. Davis-Stober

Fundamental choice axioms, such as transitivity of preference, provide testable conditions for determining whether human decision making is rational, i.e., consistent with a utilit…

stat.ME2022

Precision education: A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data

Tianyu Pan, Weining Shen, Clintin P. Davis-Stober +1

We propose a novel nonparametric Bayesian IRT model in this paper by introducing the clustering effect at question level and further assume heterogeneity at examinee level under ea…

stat.CO2018★ 38 cited

Multinomial Models with Linear Inequality Constraints: Overview and Improvements of Computational Methods for Bayesian Inference

Daniel W. Heck, Clintin P. Davis-Stober

Many psychological theories can be operationalized as linear inequality constraints on the parameters of multinomial distributions (e.g., discrete choice analysis). These constrain…

math.OC2017

Extended Formulations for Order Polytopes through Network Flows

Clintin P. Davis-Stober, Jean-Paul Doignon, Samuel Fiorini +2

Mathematical psychology has a long tradition of modeling probabilistic choice via distribution-free random utility models and associated random preference models. For such models,…

cs.SI2014

When is a crowd wise?

Clintin Davis-Stober, David Budescu, Jason Dana +1

Numerous studies and anecdotes demonstrate the "wisdom of the crowd," the surprising accuracy of a group's aggregated judgments. Less is known, however, about the generality of cro…