
Proximal mediation analysis
A common concern when trying to draw causal inferences from observationa...
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Proximal Causal Inference for Complex Longitudinal Studies
A standard assumption for causal inference about the joint effects of ti...
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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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The Proximal ID Algorithm
Unobserved confounding is a fundamental obstacle to establishing valid c...
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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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An Introduction to Proximal Causal Learning
A standard assumption for causal inference from observational data is th...
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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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Conditional separable effects
Researchers are often interested in treatment effects on outcomes that a...
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Generalized interpretation and identification of separable effects in competing event settings
In competing event settings, a counterfactual contrast of causespecific...
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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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A Semiparametric Approach to Modelbased Sensitivity Analysis in Observational Studies
When drawing causal inference from observational data, there is always c...
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Comment on "Blessings of Multiple Causes"
The premise of the deconfounder method proposed in "Blessings of Multipl...
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Semiparametric Inference for Nonmonotone MissingNotatRandom Data: the No SelfCensoring Model
We study the identification and estimation of statistical functionals of...
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Marginal Structural Models for Timevarying Endogenous Treatments: A TimeVarying Instrumental Variable Approach
Robins (1998) introduced marginal structural models (MSMs), a general cl...
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Doubly Robust Regression Analysis for Data Fusion
This paper investigates the problem of making inference about a parametr...
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A general approach to detect gene (G)environment (E) additive interaction leveraging GE independence in casecontrol studies
It is increasingly of interest in statistical genetics to test for the p...
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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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The choice to define competing risk events as censoring events and implications for causal inference
In failuretime settings, a competing risk event is any event that makes...
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The generalized frontdoor criterion for estimation of indirect causal effects of a confounded treatment
The population intervention effect (PIE) of an exposure measures the exp...
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Eric J. Tchetgen Tchetgen
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