Estimating Causal Effects for Binary Outcomes Using Per-Decision Inverse Probability Weighting
用逐决策逆概率加权估计二元结局因果效应
Micro-randomized trials are commonly conducted for optimizing mobile health interventions such as push notifications for behavior change. In analyzing such trials, causal excursion effects are often of primary interest, and their estimation typically involves inverse probability weighting (IPW). However, in a micro-randomized trial, additional treatments can often occur during the time window over which an outcome is defined, and this can greatly inflate the variance of the…