6 citations · 11 across the 5 of their papers we have counts for
5 papers
A Multiplicative Instrumental Variable Model for Data Missing Not-at-Random
Yunshu Zhang, Chan Park, Jiewen Liu +4
Instrumental variable (IV) methods offer a valuable approach to account for outcome data missing not-at-random. A valid missing data instrument is a measured factor which (i) predi…
Inference on Nonlinear Counterfactual Functionals under a Multiplicative IV Model
Yonghoon Lee, Mengxin Yu, Jiewen Liu +4
Instrumental variable (IV) methods play a central role in causal inference, particularly in settings where treatment assignment is confounded by unobserved variables. IV methods ha…
The Multiplicative Instrumental Variable Model
Jiewen Liu, Chan Park, Yonghoon Lee +4
The instrumental variable (IV) design is a common approach to address hidden confounding bias. For validity, an IV must impact the outcome only through its association with the tre…
Minimax rates for heterogeneous causal effect estimation
Edward H. Kennedy, Sivaraman Balakrishnan, James M. Robins +1
Estimation of heterogeneous causal effects - i.e., how effects of policies and treatments vary across subjects - is a fundamental task in causal inference. Many methods for estimat…
A proof of Bell's inequality in quantum mechanics using causal interactions
James M. Robins, Tyler J. VanderWeele, Richard D. Gill
We give a simple proof of Bell's inequality in quantum mechanics which, in conjunction with experiments, demonstrates that the local hidden variables assumption is false. The proof…