A Monte Carlo EM algorithm for random-coefficient-based dropout models

DOI10.1080/0266476022000006711zbMath1121.62503OpenAlexW2023924341WikidataQ58618871 ScholiaQ58618871MaRDI QIDQ3591762

James Carpenter, Claudio J. Verzilli

Publication date: 11 September 2007

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

Full work available at URL: https://doi.org/10.1080/0266476022000006711

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Nonignorable dropout models for longitudinal binary data with random effects: an application of Monte Carlo approximation through the Gibbs output ⋮ Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches

Uses Software

• GLIM

Cites Work

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• Monte Carlo EM with importance reweighting and its applications in random effects models.
• Maximum Likelihood Algorithms for Generalized Linear Mixed Models
• Modeling the Drop-Out Mechanism in Repeated-Measures Studies

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