
Doubly robust capturerecapture methods for estimating population size
Estimation of population size using incomplete lists (also called the ca...
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Semiparametric Sensitivity Analysis: Unmeasured Confounding In Observational Studies
Establishing causeeffect relationships from observational data often re...
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Comment on "Statistical Modeling: The Two Cultures" by Leo Breiman
Motivated by Breiman's rousing 2001 paper on the "two cultures" in stati...
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Doubly robust confidence sequences for sequential causal inference
This paper derives timeuniform confidence sequences (CS) for causal eff...
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Median Optimal Treatment Regimes
Optimal treatment regimes are personalized policies for making a treatme...
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Semiparametric counterfactual density estimation
Causal effects are often characterized with averages, which can give an ...
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Doubly Robust Adaptive LASSO for Effect Modifier Discovery
Effect modification occurs when the effect of the treatment on an outcom...
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Fairness in Risk Assessment Instruments: PostProcessing to Achieve Counterfactual Equalized Odds
Algorithmic fairness is a topic of increasing concern both within resear...
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Counterfactual Predictions under Runtime Confounding
Algorithms are commonly used to predict outcomes under a particular deci...
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Discussion of "On nearly assumptionfree tests of nominal confidence interval coverage for causal parameters estimated by machine learning"
We congratulate the authors on their exciting paper, which introduces a ...
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Optimal doubly robust estimation of heterogeneous causal effects
Heterogeneous effect estimation plays a crucial role in causal inference...
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Sensitivity Analysis via the Proportion of Unmeasured Confounding
In observational studies, identification of ATEs is generally achieved b...
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Causal Inference for Comprehensive Cohort Studies
In a comprehensive cohort study of two competing treatments (say, A and ...
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Counterfactual Risk Assessments, Evaluation, and Fairness
Algorithmic risk assessments are increasingly used to help humans make d...
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Incremental Intervention Effects in Studies with Many Timepoints, Repeated Outcomes, and Dropout
Modern longitudinal studies feature data collected at many timepoints, o...
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Instrumental Variable Methods using Dynamic Interventions
Recent work on dynamic interventions has greatly expanded the range of c...
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Visually Communicating and Teaching Intuition for Influence Functions
Estimators based on influence functions (IFs) have been shown effective ...
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A nonparametric projectionbased estimator for the probability of causation, with application to water sanitation in Kenya
Current estimation methods for the probability of causation (PC) make st...
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Causal effects based on distributional distances
We develop a novel framework for estimating causal effects based on the ...
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Efficient nonparametric causal inference with missing exposure information
In this note we study identifiability and efficient estimation of causal...
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Sharp instruments for classifying compliers and generalizing causal effects
It is wellknown that, without restricting treatment effect heterogeneit...
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Nonparametric Double Robustness
Use of nonparametric techniques (e.g., machine learning, kernel smoothin...
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Edward H Kennedy
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