Unveiling the Unobservable: Causal Inference on Multiple Derived Outcomes

• Published in: Journal of the American Statistical Association Vol. 119; no. 547; pp. 2178 - 2189
• Main Authors: Qiu, Yumou, Sun, Jiarui, Zhou, Xiao-Hua
• Format: Journal Article
• Language: English
• Published: Alexandria Taylor & Francis 02.07.2024; Taylor & Francis Ltd
• Subjects: Autism; brain; Brain functional connectivity; case studies; Causal inference; Correlation; drug therapy; Drugs; fMRI data; Functional connectivity; Functional magnetic resonance imaging; High dimensionality; Inference; Multiple testing procedure; Parameter estimation; Parameter identification; Propensity; Statistics; Weighting

In many applications, the interest is in treatment effects on random quantities of subjects, where those random quantities are not directly observable but can be estimated based on data from each subject. In this article, we propose a general framework for conducting causal inference in a hierarchic...