Bayesian Semiparametric Longitudinal Drift-Diffusion Mixed Models for Tone Learning in Adults

DOI10.1080/01621459.2020.1801448zbMath1510.62448arXiv1912.02774OpenAlexW3084113914MaRDI QIDQ6044618

Unnamed Author, Unnamed Author, Unnamed Author, Abhra Sarkar

Publication date: 22 May 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.02774

zbMATH Keywords

local clusteringdrift-diffusion modelsinverse Gaussian distributionsperceptual decision makinglongitudinal mixed modelsauditory category/tone learning

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Applications of statistics to psychology (62P15)

Cites Work

• Unnamed Item
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• Fast and accurate calculations for first-passage times in Wiener diffusion models
• Bayesian nonparametric modeling for functional analysis of variance
• Hierarchical Bayes models for response time data
• The accumulator model of two-choice discrimination
• A practical guide to splines
• Factorial hidden Markov models
• Slice sampling. (With discussions and rejoinder)
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Applied functional data analysis. Methods and case studies
• Semiparametric Bayes analysis of longitudinal data treatment models
• Inference in hidden Markov models.
• A Bayesian race model for response times under cyclic stimulus discriminability
• Finite mixture and Markov switching models.
• On the half-Cauchy prior for a global scale parameter
• Hybrid Dirichlet Mixture Models for Functional Data
• Functional Mixed Effects Models
• The Dirichlet labeling process for clustering functional data
• Bayesian Inference in Semiparametric Mixed Models for Longitudinal Data
• Bayesian analysis of covariance matrices and dynamic models for longitudinal data
• Bayesian Methods for Hidden Markov Models
• Informed Proposals for Local MCMC in Discrete Spaces
• The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)