Detecting multiple random changepoints in Bayesian piecewise growth mixture models

DOI10.1007/s11336-017-9594-5zbMath1422.62357arXiv1710.10626OpenAlexW2766211231WikidataQ47575936 ScholiaQ47575936MaRDI QIDQ2318826

Eric F. Lock, Nidhi Kohli, Maitreyee Bose

Publication date: 16 August 2019

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.10626

zbMATH Keywords

longitudinal dataMarkov chain Monte Carlomixture modelBayesianpiecewise functionnonlinear random effects models

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05) Applications of statistics to psychology (62P15)

Related Items (2)

BayesianPGMM ⋮ Multivariate piecewise joint models with random change-points for skewed-longitudinal and survival data

Uses Software

• BUGS
• rjags
• GitHub

Cites Work

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• Nonconjugate Bayesian Estimation of Covariance Matrices and Its Use in Hierarchical Models
• Bayesian Measures of Model Complexity and Fit
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• Random change point models: investigating cognitive decline in the presence of missing data
• Handling the Label Switching Problem in Latent Class Models Via the ECR Algorithm
• Conditional Akaike information for mixed-effects models
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
• A new look at the statistical model identification

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