activity
20182022
most citedCopula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding

4 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

stat.ME2022★ 1 cited

Sensitivity to Unobserved Confounding in Studies with Factor-structured Outcomes

Jiajing Zheng, Jiaxi Wu, Alexander D'Amour +1

In this work, we propose an approach for assessing sensitivity to unobserved confounding in studies with multiple outcomes. We demonstrate how prior knowledge unique to the multi-o…

stat.ME2021★ 1 cited

Bayesian Inference and Partial Identification in Multi-Treatment Causal Inference with Unobserved Confounding

Jiajing Zheng, Alexander D'Amour, Alexander Franks

In causal estimation problems, the parameter of interest is often only partially identified, implying that the parameter cannot be recovered exactly, even with infinite data. Here,…

stat.ME2021★ 4 cited

Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding

Jiajing Zheng, Alexander D'Amour, Alexander Franks

Recent work has focused on the potential and pitfalls of causal identification in observational studies with multiple simultaneous treatments. Building on previous work, we show th…

math.RA2018

Weighted infinitesimal unitary bialgebras, pre-Lie, matrix algebras and polynomial algebras

Yi Zhang, Jiawen Zheng, Yanfeng Luo

Motivated by the classical comatrix coalgebra, we introduce the concept of a Newtonian comatrix coalgebra. We construct an infinitesimal unitary bialgebra on a matrix algebra and a…

math.RA2018

Weighted infinitesimal unitary bialgebras on matrix algebras and weighted associative Yang-Baxter equations

Yi Zhang, Xing Gao, Jia-wen Zheng

We equip a matrix algebra with a weighted infinitesimal unitary bialgebraic structure, via a construction of a suitable coproduct. Furthermore, an infinitesimal unitary Hopf algebr…