Bias Introduced by Rounding in Multiple Imputation for Ordered Categorical Variables

DOI10.1080/00031305.2016.1200486OpenAlexW2431448603WikidataQ58142948 ScholiaQ58142948MaRDI QIDQ5884467

Yanyun Yang, Yan Xia

Publication date: 21 March 2023

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00031305.2016.1200486

zbMATH Keywords

ordinal variablemissing completely at randomnonresponse

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Robust inference when combining inverse-probability weighting and multiple imputation to address missing data with application to an electronic health records-based study of bariatric surgery ⋮ Archetypal Analysis With Missing Data: See All Samples by Looking at a Few Based on Extreme Profiles

Uses Software

• SAS
• SAS/STAT

Cites Work

• Unnamed Item
• Unnamed Item
• Multiple Imputation for Interval Estimation From Simple Random Samples With Ignorable Nonresponse
• Rounding Strategies for Multiply Imputed Binary Data
• A Potential for Bias When Rounding in Multiple Imputation
• Multiple imputation of discrete and continuous data by fully conditional specification

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