A Systematic Survey of the Optimal Strategy for Dealing With Missing Binary Outcomes in Simulation Studies of Randomized Controlled Trials

Simulation studies address methods to deal with MBOD in RCTs, provided evidence that the MI approach is superior with respect to bias and coverage compared with CCA. Non-model-based single imputation generally performed poorly.

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Publication Details

Journal
Journal of Evidence-Based Medicine
Published
2025-08-26
DOI
https://doi.org/10.1111/jebm.70058
Primary Topic
Statistical Methods and Bayesian Inference
Type
article
Field-Weighted Citation Impact
0.00

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article

A Systematic Survey of the Optimal Strategy for Dealing With Missing Binary Outcomes in Simulation Studies of Randomized Controlled Trials

Qiang Zong, Xinyao Wang, Y. Zeng, Jinhui Ma et al.
Journal of Evidence-Based Medicine
Statistical Methods and Bayesian Inference
article

A Systematic Survey of the Optimal Strategy for Dealing With Missing Binary Outcomes in Simulation Studies of Randomized Controlled Trials

Qiang Zong, Xinyao Wang, Y. Zeng, Jinhui Ma, Yanjiao Shen, Xiaoyi Su, S W Liu, Beichuan Wang, Qiong Guo, Zhengchi Li, Yamin Chen, Ying He, X. M. Xia, Xiaohong Gu, Yuqing Zhang, Jin Huang, Le Wang, Na Zhang, Qiukui Hao, Wenbo He, Liang Du, Zhi Qiao, Qingyang Shi, Xinyu Zou, Glenn L. Gordon, Parpia Sameer
article en

Abstract

Simulation studies address methods to deal with MBOD in RCTs, provided evidence that the MI approach is superior with respect to bias and coverage compared with CCA. Non-model-based single imputation generally performed poorly.

Journal of Evidence-Based MedicineVol. 18(3)
Central South University (CN), Hong Kong Polytechnic University (HK), University of Groningen (NL), Sichuan University (CN), West China Medical Center of Sichuan University (CN), ACT Foundation (US), West China Hospital of Sichuan University (CN), Second Xiangya Hospital of Central South University (CN), Impact (CA), McMaster University (CA)
National Natural Science Foundation of China
Openalex Percentile: Top 79%
Statistical Methods and Bayesian Inference
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