A comparison of multiple imputation strategies for handling missing data in multi-item scales: guidance for longitudinal studies

DOI10.1002/sim.9088zbMATH Open1546.62513MaRDI QIDQ6627963

Cattram D. Nguyen, Katherine J. Lee, Jemishabye Apajee, Rheanna M. Mainzer, John B. Carlin

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

missing datamultiple imputationlongitudinal studymulti-item scale

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

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• What is meant by ``missing at random?
• A principal component method to impute missing values for mixed data
• Principal component analysis: a review and recent developments
• Inference and missing data
• An Introduction to Statistical Learning
• Strategies for handling missing data in longitudinal studies with questionnaires
• A Potential for Bias When Rounding in Multiple Imputation
• Flexible Imputation of Missing Data, Second Edition
• Using simulation studies to evaluate statistical methods

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