Multiple imputation approaches for handling incomplete three-level data with time-varying cluster-memberships
From MaRDI portal
Publication:6628567
DOI10.1002/sim.9515zbMATH Open1547.62519MaRDI QIDQ6628567
John B. Carlin, Katherine J. Lee, Anurika Priyanjali De Silva, Unnamed Author, Margarita Moreno-Betancur
Publication date: 29 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
clustered datamissing datamultiple imputationcross-classified datathree-level datatime-varying cluster memberships
Cites Work
- Unnamed Item
- Multiple imputation for multilevel data with continuous and binary variables
- Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials
- Multiple imputation methods for handling incomplete longitudinal and clustered data where the target analysis is a linear mixed effects model
- Fully conditional specification in multivariate imputation
- Multilevel models with multivariate mixed response types
- Missing data techniques for multilevel data: implications of model misspecification
- Rounding non-binary categorical variables following multivariate normal imputation: evaluation of simple methods and implications for practice
- Flexible Imputation of Missing Data, Second Edition
- Using simulation studies to evaluate statistical methods
- A comparison of multiple-imputation methods for handling missing data in repeated measurements observational studies
This page was built for publication: Multiple imputation approaches for handling incomplete three-level data with time-varying cluster-memberships