Working Paper · 2026
Introduces Gaussian process regression (GPR) as a complement to standard linear models in political science, combining theoretical structure with flexibility about functional …
Working Paper · 2026
Introduces the Big Five Adaptive Inventory (BF-AI), a freely available computerized adaptive test built on the 100-item IPIP-NEO via the catSurv R package. In simulation studies …
PSRM · 2026
Examines how political polarization and populism shape the emotional responses of citizens to election outcomes. The study finds that while polarization amplifies emotional …
Working Paper · 2026
Proposes GD-GPIRT, a generalized dynamic Gaussian process item response theory model for longitudinal and ordinal observations. The model combines Bayesian nonparametric IRT — …
NeurIPS · 2024
Personality psychology has long been caught between two competing visions: models that describe everyone the same way, and models tailored uniquely to each individual. This paper …
AIStats · 2023
Introduces a Gaussian process framework for estimating treatment effects that vary over time in panel data. The multi-task approach borrows strength across units and time periods, …
PA · 2023
Standard political measurement tools assume that people who give the same answer do so for the same reason — but what if a liberal and a conservative both vote "no" for completely …
PA · 2022
Develops a dynamic Bayesian model for forecasting US Senate elections that integrates polling data, contextual factors, and temporal dynamics. The approach outperforms simpler …
Cambridge University Press · 2022
Survey research has a fundamental tension: asking enough questions to measure something well versus not exhausting or losing respondents. This book introduces a smarter solution — …
R package for Bayesian estimation of the generalized graded unfolding model (GGUM) via Metropolis-coupled MCMC. Recovers ideal points in settings where respondents with opposing …