6 papers
Causal Inference for All: Marginal Estimands for Outcomes Truncated by Death
Ruixuan Zhao, Mats Stensrud, Linbo Wang
In longitudinal studies, outcomes of interest are often truncated by death, meaning that they are only observed or well-defined conditional on intercurrent events such as survival.…
Estimating the Wasserstein barycenter of one-dimensional distributions under sparse sampling
James Peng, Florian Stijven, Linbo Wang +1
We study distributional data under sparse sampling where each unit is represented by a probability distribution on the real line observed only through a small i.i.d.~sample. A natu…
Order Dependence in Regression by Composition: Discussion on "Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt
Mei Dong, Linbo Wang, Lin Liu +1
We discuss the regression-by-composition framework of Farewell, Daniel, Stensrud and Huitfeldt, highlighting a key consequence of its sequential construction: order dependence. Reo…
A Parameter-Centric View on Regression
Jingxin Yan, Lin Liu, Oliver Dukes +2
Discussion on ``Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt
Toward Variation-Independent Regression by Composition
Ruixuan Zhao, Oliver Dukes, Linbo Wang +1
Discussion on "Regression by Composition" by Farewell, Daniel, Stensrud, and Huitfeldt.
Simultaneous Estimation of Multiple Treatment Effects from Observational Studies
Xiaochuan Shi, Dehan Kong, Linbo Wang
Unmeasured confounding presents a significant challenge in causal inference from observational studies. Classical approaches often rely on collecting proxy variables, such as instr…