Impute the missing data using retrieved dropouts

• Published in: BMC medical research methodology Vol. 22; no. 1; pp. 82 - 15
• Main Authors: Wang, Shuai, Hu, Haoyan
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 27.03.2022; BioMed Central; BMC
• Subjects: Clinical trials; Data Interpretation, Statistical; Datasets; Humans; Hypotheses; ICH E9 (R1); Medical research; Medicine, Experimental; Methods; Missing data; Missing not at random; Multiple imputation; Regulatory agencies; Research Design; Research methodology; Retrieved dropouts; Statistical methods; Treatment policy; United States; ICH E9 (R1); Retrieved dropouts; Missing not at random; Multiple imputation; Treatment policy

In the past few decades various methods have been proposed to handle missing data of clinical studies, so as to assess the robustness of primary results. Some of the methods are based on the assumption of missing at random (MAR) which assumes subjects who discontinue the treatment will maintain the...