Evidence accumulation models with R: A practical guide to hierarchical Bayesian methods
Evidence accumulation models are a useful tool to allow researchers to investigate the latent cognitive variables that underlie response time and response accuracy. However, applying evidence accumulation models can be difficult because they lack easily computable forms. Numerical methods are requir...
Main Authors: | Lin, Yi-Shin, Strickland, Luke |
---|---|
Format: | Article |
Language: | English |
Published: |
Université d'Ottawa
2020-04-01
|
Series: | Tutorials in Quantitative Methods for Psychology |
Subjects: | |
Online Access: | https://www.tqmp.org/RegularArticles/vol16-2/p133/p133.pdf |
Similar Items
-
Bayesian Hierarchical Modeling and Markov Chain Simulation for Chronic Wasting Disease
by: Mehl, Christopher
Published: (2016) -
Sampling approaches in Bayesian computational statistics with R
by: Sun, Wenwen
Published: (2010) -
Bayesian multivariate spatial models and their applications
by: Song, Joon Jin
Published: (2004) -
Hierarchical Modeling for Diagnostic Test Accuracy Using Multivariate Probability Distribution Functions
by: Johny Pambabay-Calero, et al.
Published: (2021-06-01) -
B2Z: R Package for Bayesian Two-Zone Models
by: João Vitor Dias Monteiro, et al.
Published: (2011-08-01)