Computational protocol for hierarchical Bayesian modeling of perception and generalization in fear conditioning. [PDF]
STAR ProtocYu K +3 more
europepmc +1 more source
Idiographic interrater reliability measures for intensive longitudinal multirater data
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Interrater reliability plays a crucial role in various areas of psychology. In this article, we propose a multilevel latent time series model for intensive longitudinal data with structurally different raters (e.g., self‐reports and partner reports).
Tobias Koch +4 more
wiley +1 more source
A physics-informed neural network approach for estimating population-level pharmacokinetic parameters from aggregated concentration data. [PDF]
J Pharmacokinet PharmacodynTsiros P, Minadakis V, Sarimveis H.
europepmc +1 more source
Power priors for latent variable mediation models under small sample sizes
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Latent variable models typically require large sample sizes for acceptable efficiency and reliable convergence. Appropriate informative priors are often required for gainfully employing Bayesian analysis with small samples. Power priors are informative priors built on historical data, weighted to account for non‐exchangeability with the ...
Lihan Chen +2 more
wiley +1 more source
Bayesian estimation of the inverse Exponential Power distribution for COVID-19 case fatality analysis under SDG 3. [PDF]
Sci RepAkdam N +4 more
europepmc +1 more source
This paper is intended to appear as a chapter for the Handbook of Markov Chain Monte Carlo. The goal of this chapter is to unify various problems at the intersection of Markov chain Monte Carlo (MCMC) and machine learning$\unicode{x2014}$which includes black-box variational inference, adaptive MCMC, normalizing flow construction and transport-assisted ...
Bouchard-Côté, Alexandre +3 more
openaire +1 more source
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Hidden Markov diagnostic classification models capture how students' cognitive attributes evolve over time. This paper introduces a Bayesian Markov chain Monte Carlo algorithm for diagnostic classification models that jointly estimates time‐varying Q matrices, latent attributes, item parameters, attribute class proportions and transition ...
Chen‐Wei Liu
wiley +1 more source
Biological causes and impacts of rugged tree landscapes in phylodynamic inference. [PDF]
Proc Natl Acad Sci U S AGao J +5 more
europepmc +1 more source
LLM‐based prior elicitation for Bayesian graphical modeling
British Journal of Mathematical and Statistical Psychology, EarlyView.ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski +2 more
wiley +1 more source
To vary or not to vary: A flexible empirical Bayes factor for testing variance components
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
wiley +1 more source