Using MCMC chain outputs to efficiently estimate Bayes factors

DOI10.1016/j.jmp.2011.06.004zbMath1270.62155OpenAlexW2105625839MaRDI QIDQ645491

Jeffrey N. Rouder, Paul L. Speckman, Michael S. Pratte, Richard D. Morey

Publication date: 15 November 2011

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmp.2011.06.004

zbMATH Keywords

Markov chain Monte CarloANOVABayesian statisticsBayesian inferenceencompassing priors

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Numerical analysis or methods applied to Markov chains (65C40) Applications of statistics to psychology (62P15)

Related Items

Error probabilities in default Bayesian hypothesis testing, Connecting and Contrasting the Bayes Factor and a Modified ROPE Procedure for Testing Interval Null Hypotheses, Objective Bayesian comparison of constrained analysis of variance models, Bain: a program for Bayesian testing of order constrained hypotheses in structural equation models, Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements, A tutorial on the Bayesian approach for analyzing structural equation models, Simple relation between Bayesian order-restricted and point-null hypothesis tests, Default Bayes factors for ANOVA designs, Bayes factors for testing order-constrained hypotheses on correlations, Bayes factor testing of equality and order constraints on measures of association in social research, The lognormal race: a cognitive-process model of choice and latency with desirable psychometric properties

Uses Software

• R
• WinBUGS
• JAGS
• BayesDA
• tsbridge

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