Showing 2023Show all
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stat.ME2023
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…
stat.ME2023
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…
stat.ME2023
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…