Comparison of maximum likelihood approach, Diggle–Kenward selection model, pattern mixture model with MAR and MNAR dropout data

DOI10.1080/03610918.2018.1506028OpenAlexW2900180600WikidataQ115926408 ScholiaQ115926408MaRDI QIDQ5086316

Hong-Yun Liu, Nan Chen, Mei-Juan Li

Publication date: 5 July 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1506028

zbMATH Keywords

maximum likelihood approachpattern mixture modellatent growth curve modelmissing not at random (MNAR)Diggle-Kenward selection model

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• Mplus
• LISREL

Cites Work

• Unnamed Item
• Sensitivity analysis of longitudinal data with intermittent missing values
• Robust growth mixture models with non-ignorable missingness: models, estimation, selection, and application
• Latent Curve Models
• Modeling Longitudinal Data with Nonignorable Dropouts Using a Latent Dropout Class Model
• Missing Data in Longitudinal Studies
• Pattern-Mixture Models for Multivariate Incomplete Data
• Informative Drop-Out in Longitudinal Data Analysis
• Modeling the Drop-Out Mechanism in Repeated-Measures Studies
• Data-driven sensitivity analysis to detect missing data mechanism with applications to structural equation modelling
• A Latent‐Class Mixture Model for Incomplete Longitudinal Gaussian Data

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