In the study of real-world data, the pragmatic randomized controlled trial can provide the optimal evidence for clinical decisions. Although randomization protects against confounding, post-randomization confounding may still arise due to non-compliance. Traditional intention-to-treat analysis will drift apart from true estimation and lead to deviation of clinical decisions. Meanwhile, the alternative traditional methods would subject to bias and confounding. Thus, new methods are required for revolution, i.e., instrument variable method and modern per-protocol analysis. Our study reviews the defects of traditional methods in pragmatic randomized controlled trials, and then refers to two new methods with a detailed discussion of strengths and weaknesses. We aim to provide researches with insights on choosing the statistical methods for pragmatic trial.
Citation： SHI Qingyang, LI Ling, LI Sheyu, SUN Xin. Statistical methods in pragmatic randomized controlled trials (I): addressing non-compliance. Chinese Journal of Evidence-Based Medicine, 2021, 21(1): 117-124. doi: 10.7507/1672-2531.202010019 Copy