1 citations · 1 across the 3 of their papers we have counts for
5 papers
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…
Identification and estimation of causal peer effects using instrumental variables
Shanshan Luo, Kang Shuai, Yechi Zhang +2
In social science researches, causal inference regarding peer effects often faces significant challenges due to homophily bias and contextual confounding. For example, unmeasured h…
Mediation analysis with unmeasured confounding between parallel mediators and outcome
Kang Shuai, Lan Liu, Yangbo He +1
Mediation analysis extending beyond single mediators has gained significant attention in recent years. However, related methods often assume the absence of unmeasured mediator-outc…
Identifying Causal Effects Using Instrumental Variables from the Auxiliary Dataset
Kang Shuai, Shanshan Luo, Wei Li +1
Instrumental variable approaches have gained popularity for estimating causal effects in the presence of unmeasured confounders. However, the availability of instrumental variables…
Identification and estimation of causal effects in the presence of confounded principal strata
Shanshan Luo, Wei Li, Wang Miao +1
The principal stratification has become a popular tool to address a broad class of causal inference questions, particularly in dealing with non-compliance and truncation-by-death p…