Sensitivity analysis for transportability in multi-study, multi-outcome settings
多研究、多结局环境下因果效应可迁移性的敏感性分析
Existing work in data fusion has covered identification of causal estimands when integrating data from heterogeneous sources. These results typically require additional assumptions to make valid estimation and inference. However, there is little literature on transporting and generalizing causal effects in multiple-outcome setting, where the primary outcome is systematically missing on the study level but for which other outcome variables may serve as proxies. We review an…