Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs
数据驱动的切换实验:理论权衡与经验贝叶斯设计
We study the design and analysis of switchback experiments conducted on a single aggregate unit. The design problem is to partition the continuous time space into intervals and switch treatments between intervals, in order to minimize the estimation error of the treatment effect. We show that the estimation error depends on four factors: carryover effects, periodicity, serially correlated outcomes, and impacts from simultaneous experiments. We derive a rigorous bias-variance…