1 citations · 2 across the 16 of their papers we have counts for
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On the Comparative Analysis of Average Treatment Effects Estimation via Data Combination
Peng Wu, Shanshan Luo, Zhi Geng
There is growing interest in exploring causal effects in target populations via data combination. However, most approaches are tailored to specific settings and lack comprehensive…
Multiply robust estimation of causal effects using linked data
Shanshan Luo, Yechi Zhang, Wei Li
Unmeasured confounding presents a common challenge in observational studies, potentially making standard causal parameters unidentifiable without additional assumptions. Given the…
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…
Identifiability of causal effects with non-Gaussianity and auxiliary covariates
Kang Shuai, Shanshan Luo, Yue Zhang +2
Assessing causal effects in the presence of unmeasured confounding is challenging. Although auxiliary variables, such as instrumental variables, are commonly used to identify causa…