Multiple imputation of missing data in clinical longitudinal studies and its sensitivity analyses / 中国临床药理学与治疗学

ABSTRACT

AIM: To guide the multiple imputation of missing data in clinical longitudinal studies and its sensitivity analyses, and highlight the importance of sensitivity analyses by taking the clinical trial of Qizhitongluo Capsule in treating ischemic stroke as an example. METHODS: To implement PROC MI process in SAS to perform multiple imputation and its sensitivity analysis. RESULTS: In the example, after multiple imputation, improvements in lower limb motor scores of the Qizhitongluo group were greater than those of the placebo group (all P<0.01), and the results of two sensitivity analyses under "missing not at random" were consistent with those under "missing at random". CONCLUSION: Multiple imputations combined with sensitivity analyses can ensure a robust result. It is recommended that clinical researchers perform sensitivity analyses after filling missing data.