Technology companies are increasingly using randomized controlled trials (RCTs) as part of their development process. Despite having fine control over engineering systems and data instrumentation, these RCTs can still be imperfectly executed. In fact, online experimentation suffers from many of the same biases seen in biomedical RCTs including opt-in and user activity bias, selection bias, non-compliance with the treatment, and more generally, challenges in the ability to test the question of interest. The result of these imperfections can lead to a bias in the estimated causal effect, a loss in statistical power, an attenuation of the effect, or even a need to reframe the question that can be answered. This paper aims to make practitioners of experimentation more aware of imperfections in technology-industry RCTs, which can be hidden throughout the engineering stack or in the design process.
翻译:技术公司越来越多地将随机控制试验(RCTs)作为其发展进程的一部分。这些RCT虽然对工程系统和数据仪表有很好的控制,但执行不力。事实上,在线实验在生物医学RCTs中有许多相同的偏差,包括选择入场和用户活动的偏差、选择偏差、不遵守治疗规定,以及更一般地说,检验利息问题的能力方面的挑战。这些不完善的结果可能导致估计因果关系的偏差、统计力的丧失、效应的减弱,甚至需要重新界定可以回答的问题。本文旨在使实验的实践者更清楚地认识到技术工业RCT的缺陷,这些缺陷可能隐藏在工程堆或设计过程中。