A Universal Framework for Factorial Matched Observational Studies with General Treatment Types: Design, Analysis, and Applications
一般处理类型的析因匹配观察性研究:设计、分析与应用
Matching is one of the most widely used causal inference frameworks in observational studies. However, all the existing matching-based causal inference methods are designed for either a single treatment with general treatment types (e.g., binary, ordinal, or continuous) or factorial (multiple) treatments with binary treatments only. To our knowledge, no existing matching-based causal methods can handle factorial treatments with general treatment types. This critical gap…