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08/18/2023
Proximal Causal Inference for Synthetic Control with Surrogates
The synthetic control method (SCM) has become a popular tool for estimat...
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08/04/2022
Using Instruments for Selection to Adjust for Selection Bias in Mendelian Randomization
Selection bias is a common concern in epidemiologic studies. In the lite...
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07/18/2022
A self-censoring model for multivariate nonignorable nonmonotone missing data
We introduce a self-censoring model for multivariate nonignorable nonmon...
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04/27/2022
Proximal Causal Inference for Marginal Counterfactual Survival Curves
Contrasting marginal counterfactual survival curves across treatment arm...
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09/24/2021
Proximal mediation analysis
A common concern when trying to draw causal inferences from observationa...
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09/15/2021
Proximal Causal Inference for Complex Longitudinal Studies
A standard assumption for causal inference about the joint effects of ti...
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09/04/2021
Identification and Estimation of Causal Peer Effects Using Double Negative Controls for Unmeasured Network Confounding
Scientists have been interested in estimating causal peer effects to und...
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08/15/2021
The Proximal ID Algorithm
Unobserved confounding is a fundamental obstacle to establishing valid c...
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03/22/2021
A New Causal Approach to Account for Treatment Switching in Randomized Experiments under a Structural Cumulative Survival Model
Treatment switching in a randomized controlled trial is said to occur wh...
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09/23/2020
An Introduction to Proximal Causal Learning
A standard assumption for causal inference from observational data is th...
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07/20/2020
A coherent likelihood parametrization for doubly robust estimation of a causal effect with missing confounders
Missing data and confounding are two problems researchers face in observ...
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06/28/2020
Conditional separable effects
Researchers are often interested in treatment effects on outcomes that a...
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04/30/2020
Generalized interpretation and identification of separable effects in competing event settings
In competing event settings, a counterfactual contrast of cause-specific...
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01/17/2020
Counterexamples to "The Blessings of Multiple Causes" by Wang and Blei
This brief note is meant to complement our previous comment on "The Bles...
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10/30/2019
A Semiparametric Approach to Model-based Sensitivity Analysis in Observational Studies
When drawing causal inference from observational data, there is always c...
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10/11/2019
Comment on "Blessings of Multiple Causes"
The premise of the deconfounder method proposed in "Blessings of Multipl...
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09/04/2019
Semiparametric Inference for Non-monotone Missing-Not-at-Random Data: the No Self-Censoring Model
We study the identification and estimation of statistical functionals of...
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09/14/2018
Marginal Structural Models for Time-varying Endogenous Treatments: A Time-Varying Instrumental Variable Approach
Robins (1998) introduced marginal structural models (MSMs), a general cl...
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08/22/2018
Doubly Robust Regression Analysis for Data Fusion
This paper investigates the problem of making inference about a parametr...
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08/18/2018
A general approach to detect gene (G)-environment (E) additive interaction leveraging G-E independence in case-control studies
It is increasingly of interest in statistical genetics to test for the p...
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08/10/2018
Estimation of natural indirect effects robust to unmeasured confounding and mediator measurement error
The use of causal mediation analysis to evaluate the pathways by which a...
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06/15/2018
The choice to define competing risk events as censoring events and implications for causal inference
In failure-time settings, a competing risk event is any event that makes...
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11/09/2017
