A randomized controlled trial (RCT) is widely regarded as the gold standard for assessing the causal effect of a treatment or intervention, assuming perfect implementation. In practice, however, randomization can be compromised for various reasons, such as one-sided noncompliance. In this paper, we address the issue of one-sided noncompliance and propose a general estimand, the complier general causal effect (CGCE), to characterize the causal effect among compliers. We further investigate the conditions under which efficient estimation of the CGCE can be achieved under minimal assumptions. Comprehensive simulation studies and a real data application are conducted to illustrate the proposed methods and to compare them with existing approaches.

翻译：随机对照试验被广泛视为评估治疗或干预因果效应的金标准，前提是实施过程完美无缺。然而在实践中，随机化可能因各种原因受到破坏，例如单侧不依从。本文针对单侧不依从问题，提出了一种通用估计量——依从者一般因果效应，用以刻画依从者群体的因果效应。我们进一步研究了在最小假设条件下实现CGCE有效估计所需满足的条件。通过全面的模拟研究和实际数据应用，展示了所提方法的有效性，并与现有方法进行了比较。