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06/06/2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning
We propose a simple and general framework for nonparametric estimation o...
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05/23/2023
Notes on Causation, Comparison, and Regression
Comparison and contrast are the basic means to unveil causation and lear...
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05/06/2023
Risk Set Matched Difference-in-Differences for the Analysis of Effect Modification in an Observational Study on the Impact of Gun Violence on Health Outcomes
Gun violence is a major problem in contemporary American society. Howeve...
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03/15/2023
lmw: Linear Model Weights for Causal Inference
The linear regression model is widely used in the biomedical and social ...
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01/15/2023
Doubly Robust Counterfactual Classification
We study counterfactual classification as a new tool for decision-making...
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09/20/2022
Counterfactual Mean-variance Optimization
We study a new class of estimands in causal inference, which are the sol...
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05/19/2022
Balanced and robust randomized treatment assignments: the Finite Selection Model
The Finite Selection Model (FSM) was proposed and developed by Carl Morr...
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03/16/2022
One-step weighting to generalize and transport treatment effect estimates to a target population
Weighting methods are often used to generalize and transport estimates o...
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03/01/2022
Privacy-Preserving and Communication-Efficient Causal Inference for Hospital Quality Measurement
Data sharing can improve hospital quality measurement, but sharing patie...
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01/12/2022
Using Cardinality Matching to Design Balanced and Representative Samples for Observational Studies
Cardinality matching is a computational method for finding the largest p...
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10/28/2021
The Balancing Act in Causal Inference
The idea of covariate balance is at the core of causal inference. Invers...
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05/20/2021
Profile Matching for the Generalization and Personalization of Causal Inferences
We introduce profile matching, a multivariate matching method for random...
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05/06/2021
Randomized and Balanced Allocation of Units into Treatment Groups Using the Finite Selection Model for R
The original Finite Selection Model (FSM) was developed in the 1970s to ...
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05/06/2021
Targeted Quality Measurement of Health Care Providers
Motivated by the problem of measuring the quality of cancer care deliver...
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04/14/2021
On the implied weights of linear regression for causal inference
In this paper, we derive and analyze the implied weights of linear regre...
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04/12/2020
Complex Discontinuity Designs Using Covariates
Regression discontinuity designs are extensively used for causal inferen...
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05/26/2019
Large Sample Properties of Matching for Balance
Matching methods are widely used for causal inference in observational s...
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10/15/2018
