
Identification and estimation of nonignorable missing outcome mean without identifying the full data distribution
We consider the problem of making inference about the population outcome...
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Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework
Synthetic control methods are commonly used to estimate the treatment ef...
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EndtoEnd Balancing for Causal Continuous TreatmentEffect Estimation
We study the problem of observational causal inference with continuous t...
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GENIUSMAWII: For Robust Mendelian Randomization with Many Weak Invalid Instruments
Mendelian randomization (MR) has become a popular approach to study caus...
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Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals
A moment function is called doubly robust if it is comprised of two nuis...
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Semiparametric proximal causal inference
Skepticism about the assumption of no unmeasured confounding, also known...
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On a necessary and sufficient identification condition of optimal treatment regimes with an instrumental variable
Unmeasured confounding is a threat to causal inference and individualize...
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On Mendelian Randomization MixedScale Treatment Effect Robust Identification (MR MiSTERI) and Estimation for Causal Inference
Standard Mendelian randomization analysis can produce biased results if ...
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A Selective Review of Negative Control Methods in Epidemiology
Purpose of Review: Negative controls are a powerful tool to detect and a...
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A Simple Weighted Approach for Instrumental Variable Estimation of Marginal Structural Mean Models
Robins 1997 introduced marginal structural models (MSMs), a general clas...
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Regressionbased Negative Control of Homophily in Dyadic Peer Effect Analysis
A prominent threat to causal inference about peer effects over social ne...
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A semiparametric instrumental variable approach to optimal treatment regimes under endogeneity
There is a fastgrowing literature on estimating optimal treatment regim...
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Biasaware model selection for machine learning of doubly robust functionals
While model selection is a wellstudied topic in parametric and nonparam...
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Multiply Robust Learning of the Average Treatment Effect with an Invalid Instrumental Variable
Instrumental variable (IV) methods have been widely used to identify cau...
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A Confounding Bridge Approach for Double Negative Control Inference on Causal Effects (Supplement and Sample Codes are included)
Unmeasured confounding is a key challenge for causal inference. Negative...
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A Confounding Bridge Approach for Double Negative Control Inference on Causal Effects
Unmeasured confounding is a key challenge for causal inference. Negative...
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Multiply Robust Causal Inference With Double Negative Control Adjustment for Unmeasured Confounding
Unmeasured confounding is a threat to causal inference in observational ...
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Learning Causal Hazard Ratio with Endogeneity
Cox's proportional hazards model is one of the most popular statistical ...
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A stochastic secondorder generalized estimating equations approach for estimating intraclass correlation coefficient in the presence of informative missing data
Design and analysis of cluster randomized trials must take into account ...
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Eric Tchetgen Tchetgen
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