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Preprint Oct 2026

Testing Treatment Effect Heterogeneity with Functional Outcomes

Assessing treatment-effect heterogeneity is important in causal inference, particularly for functional outcomes where effects may vary over time and the common effect is unknown. We propose a nonparametric procedure that assesses treatment-effect homogeneity through a testable marginal implication. By comparing within-...

Yong-Zhen Feng, Jie Li, Xiao-Jun Song · 0 citations

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