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20182026
most citedAn Introduction to Proximal Causal Learning

36 citations · 44 across the 14 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

stat.ME2022

Proximal Survival Analysis to Handle Dependent Right Censoring

Andrew Ying

Many epidemiological and clinical studies aim at analyzing a time-to-event endpoint. A common complication is right censoring. In some cases, it arises because subjects are still s…

stat.ME2022★ 6 cited

Doubly Robust Estimation under Covariate-Induced Dependent Left Truncation

Yuyao Wang, Andrew Ying, Ronghui Xu

In prevalent cohort studies with follow-up, the time-to-event outcome is subject to left truncation leading to selection bias. For estimation of the distribution of time-to-event,…

stat.ME2022

Causal Identification for Complex Functional Longitudinal Studies

Andrew Ying

Real-time monitoring in modern medical research introduces functional longitudinal data, characterized by continuous-time measurements of outcomes, treatments, and confounders. Thi…

stat.ME2022★ 1 cited

Proximal Causal Inference for Marginal Counterfactual Survival Curves

Andrew Ying, Yifan Cui, Eric J. Tchetgen Tchetgen

Contrasting marginal counterfactual survival curves across treatment arms is an effective and popular approach for inferring the causal effect of an intervention on a right-censore…

stat.ME2022

A Robust Instrumental Variable Method Accounting for Treatment Switching in Open-Label Randomized Controlled Trials

Andrew Ying

In a randomized controlled trial, treatment switching (also called contamination or crossover) occurs when a patient initially assigned to one treatment arm changes to another arm…

stat.ME2022★ 1 cited

Marginal Structural Illness-Death Models for Semi-Competing Risks Data

Yiran Zhang, Andrew Ying, Steve Edland +2

The three state illness death model has been established as a general approach for regression analysis of semi competing risks data. For observational data the marginal structural…