1 citations · 1 across the 5 of their papers we have counts for
5 papers
Bayesian Inference for Evidence Accumulation Models with Regressors
Viet Hung Dao, David Gunawan, Robert Kohn +3
Evidence accumulation models (EAMs) are an important class of cognitive models used to analyze both response time and response choice data recorded from decision-making tasks. Deve…
Identifying relationships between cognitive processes across tasks, contexts, and time
Laura Wall, David Gunawan, Scott D. Brown +3
It is commonly assumed that a specific testing occasion (task, design, procedure, etc.) provides insights that generalise beyond that occasion. This assumption is infrequently care…
Time-evolving psychological processes over repeated decisions
David Gunawan, Guy E. Hawkins, Robert Kohn +2
Many psychological experiments have subjects repeat a task to gain the statistical precision required to test quantitative theories of psychological performance. In such experiment…
Robustly estimating the marginal likelihood for cognitive models via importance sampling
Minh-Ngoc Tran, Marcel Scharth, David Gunawan +3
Recent advances in Markov chain Monte Carlo (MCMC) extend the scope of Bayesian inference to models for which the likelihood function is intractable. Although these developments al…
New Estimation Approaches for the Hierarchical Linear Ballistic Accumulator Model
David Gunawan, Guy E. Hawkins, Minh-Ngoc Tran +2
The Linear Ballistic Accumulator (Brown & Heathcote, 2008) model is used as a measurement tool to answer questions about applied psychology. The analyses based on this model depend…