Using multiple imputation with GEE with non-monotone missing longitudinal binary outcomes

DOI10.1007/s11336-020-09729-yzbMath1477.62345OpenAlexW3090312687WikidataQ100419788 ScholiaQ100419788MaRDI QIDQ2065247

Garrett M. Fitzmaurice, Stuart R. Lipsitz, Roger D. Weiss

Publication date: 7 January 2022

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855014

zbMATH Keywords

generalized estimating equationsmissing at randommissing completely at randommultivariate normalfully conditional specification

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15) Missing data (62D10)

Uses Software

• SAS
• gee
• MICE
• SAS/STAT

Cites Work

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• A Three-Stage Estimator for Studies with Repeated and Possibly Missing Binary Outcomes
• Performance of Generalized Estimating Equations in Practical Situations
• A Potential for Bias When Rounding in Multiple Imputation
• Multiple imputation of discrete and continuous data by fully conditional specification

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