Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials

DOI10.1002/bimj.201000140zbMath1207.62193OpenAlexW1976891556WikidataQ35073123 ScholiaQ35073123MaRDI QIDQ3084181

Rebecca R. Andridge

Publication date: 15 March 2011

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3124925

zbMATH Keywords

missing data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Analysis of variance and covariance (ANOVA) (62J10) Estimation in survival analysis and censored data (62N02) Testing in survival analysis and censored data (62N03)

Related Items (2)

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Uses Software

• R
• Stata
• SAS
• MICE
• SAS/STAT

Cites Work

• Unnamed Item
• Cluster randomization trials in epidemiology: Theory and application
• Finite sample properties of multiple imputation estimators.
• Missing Data, Imputation, and the Bootstrap
• Multiple Imputation for Interval Estimation From Simple Random Samples With Ignorable Nonresponse
• The Effect of Two-Stage Sampling on Ordinary Least Squares Methods
• Miscellanea. Small-sample degrees of freedom with multiple imputation
• A Potential for Bias When Rounding in Multiple Imputation

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