Random effects regression mixtures for analyzing infant habituation

DOI10.1080/02664763.2014.1000272OpenAlexW2063148890MaRDI QIDQ5130258

Derek S. Young, David R. Hunter

Publication date: 4 November 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://figshare.com/articles/journal_contribution/Random_effects_regression_mixtures_for_analyzing_infant_habituation/1287768

zbMATH Keywords

bootstraplikelihood ratio testECM algorithmswitching regressionstrajectory data

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to psychology (62P15)

Related Items (3)

Comparison of the EM, CEM and SEM algorithms in the estimation of finite mixtures of linear mixed models: a simulation study ⋮ Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering ⋮ The Mixturegram: A Visualization Tool for Assessing the Number of Components in Finite Mixture Models

Uses Software

• Mplus
• mixtools
• bootstrap

Cites Work

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• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• A Modified Likelihood Ratio Test for Homogeneity in Finite Mixture Models
• Mixtures
• A Linear Mixed-Effects Model With Heterogeneity in the Random-Effects Population
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Statistical analysis of finite mixture distributions
• Finite mixture models
• A New Approach to Estimating Switching Regressions

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