Synthesizing Evidence: Data-Pooling as a Tool for Treatment Selection in Online Experiments
综合证据:利用在线实验数据汇集选择处理方案
Randomized experiments are the gold standard for causal inference but face significant challenges in business applications, including limited traffic allocation, the need for heterogeneous treatment effect estimation, and the complexity of managing overlapping experiments. These factors lead to high variability in treatment effect estimates, making data-driven policy roll out difficult. To address these issues, we introduce the data pooling treatment roll-out (DPTR)…