1 citations · 2 across the 16 of their papers we have counts for
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Orthogonal Policy Learning with Ordinal Outcomes
Yue Zhang, Shanshan Luo, Yangbo He
Policy learning methods based on conditional average treatment effects can obscure subpopulation heterogeneity when applied to ordinal outcomes. We develop a policy learning framew…
Selecting among Missingness Models for Sequential Outcomes with Nonignorable Nonresponse
Yingying Wang, Yuan Liu, Shanshan Luo
Sequential outcomes in longitudinal studies and multi-wave surveys may be missing not at random at both earlier and later occasions. We study graphical models in which at least one…
Mediation Analysis with Multiple Mediators Subject to Missing Not at Random
Yanfei Jin, Shanshan Luo, Xueli Wang +1
Causal mediation analysis serves as a key tool for uncovering the mediating mechanisms linking treatments to outcomes. Existing methods for mediation analysis with multiple mediato…
Apportioning Causal Responsibility of Two Risk Factors for an Adverse Outcome via Counterfactual Attribution
Shanshan Luo, Yafang Deng, Qingyuan Zhao +1
Unlike traditional causal inference, which prospectively evaluates the effects of causes, apportioning causal responsibility requires a retrospective assessment to deduce the cause…
Assessing Interactive Causes of an Occurred Outcome Due to Two Binary Exposures
Shanshan Luo, Wei Li, Xueli Wang +2
In contrast to evaluating treatment effects, causal attribution analysis focuses on identifying the key factors responsible for an observed outcome. For two binary exposure variabl…