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Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects

https://doi.org/10.2139/ssrn.4746623
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Doubly robust uniform confidence band for the conditional average treatment effect function
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Subgroup identification based on differential effect search—A recursive partitioning method for establishing response to treatment in patient subpopulations
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Statistics for High-Dimensional Data
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Subgroup analysis and other (mis)uses of baseline data in clinical trials
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Metalearners for estimating heterogeneous treatment effects using machine learning
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Benign overfitting in linear regression
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Sensitivity analysis of individual treatment effects: A robust conformal inference approach
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Ridge Regression: Biased Estimation for Nonorthogonal Problems
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Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
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Tree-structured analysis of treatment effects with large observational data
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Estimating Conditional Average Treatment Effects
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Post-Selection Inference for Generalized Linear Models With Many Controls
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Estimation of Conditional Average Treatment Effects With High-Dimensional Data
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Double machine learning methods for estimating average treatment effects: a comparative study
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A Tree-Based Semi-Varying Coefficient Model for the COM-Poisson Distribution
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The central role of the propensity score in observational studies for causal effects
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Quasi-oracle estimation of heterogeneous treatment effects
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Uniform post-selection inference for least absolute deviation regression and other Z-estimation problems
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Should All Smokers Use Combination Smoking Cessation Pharmacotherapy? Using Novel Analytic Methods to Detect Differential Treatment Effects Over 8 Weeks of Pharmacotherapy
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Estimation of Heterogeneous Treatment Effects from Randomized Experiments, with Application to the Optimal Planning of the Get-Out-the-Vote Campaign
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Representation Learning: A Review and New Perspectives
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Consistent tests for conditional treatment effects
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Double/debiased machine learning for treatment and structural parameters
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Regularization and Variable Selection Via the Elastic Net
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Structural Equations, Treatment Effects, and Econometric Policy Evaluation1
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Doubly Robust Estimation in Missing Data and Causal Inference Models
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Regression Shrinkage and Selection Via the Lasso
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Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
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Optimal Statistical Inference for Individualized Treatment Effects in High-Dimensional Models
inferredcites →https://doi.org/10.1198/106186008x319331openalex-extracted
Model-Based Recursive Partitioning
inferredcites →https://doi.org/10.1198/jcgs.2010.08162openalex-extracted
Bayesian Nonparametric Modeling for Causal Inference
inferredcites →https://doi.org/10.1214/009053606000000281openalex-extracted
High-dimensional graphs and variable selection with the Lasso
inferredcites →https://doi.org/10.1214/009053607000000929openalex-extracted
High-dimensional generalized linear models and the lasso
inferredcites →https://doi.org/10.1214/12-aoas593openalex-extracted
Estimating treatment effect heterogeneity in randomized program evaluation
inferredcites →https://doi.org/10.1214/14-aos1221openalex-extracted
On asymptotically optimal confidence regions and tests for high-dimensional models
inferredcites →https://doi.org/10.1214/16-aos1461openalex-extracted
Confidence intervals for high-dimensional linear regression: Minimax rates and adaptivity
inferredcites →https://doi.org/10.1214/17-aos1630openalex-extracted
Debiasing the lasso: Optimal sample size for Gaussian designs
inferredcites →https://doi.org/10.1214/18-aos1698openalex-extracted
Covariate balancing propensity score by tailored loss functions
inferredcites →https://doi.org/10.1214/18-aos1709openalex-extracted
Generalized random forests
inferredcites →https://doi.org/10.1214/19-aos1875openalex-extracted
Nonparametric regression using deep neural networks with ReLU activation function
inferredcites →https://doi.org/10.1214/aos/1176350609openalex-extracted
Consistent Estimation of the Influence Function of Locally Asymptotically Linear Estimators
inferredcites →https://doi.org/10.1257/jep.28.2.29openalex-extracted
High-Dimensional Methods and Inference on Structural and Treatment Effects
inferredcites →https://doi.org/10.2139/ssrn.3048177openalex-extracted
Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects
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Statistical Inference for Variable Importance
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Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme
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On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
inferredcites →https://doi.org/10.48550/arxiv.0912.4045openalex-extracted
Restricted Eigenvalue Conditions on Subgaussian Random Matrices
inferredcites →https://doi.org/10.48550/arxiv.1306.3171openalex-extracted
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
inferredcites →https://doi.org/10.48550/arxiv.1605.03661openalex-extracted
Learning Representations for Counterfactual Inference
inferredcites →https://doi.org/10.48550/arxiv.1606.03976openalex-extracted
Estimating individual treatment effect: generalization bounds and algorithms
inferredcites →https://doi.org/10.48550/arxiv.1608.08925openalex-extracted
Recursive Partitioning for Personalization using Observational Data
inferredcites →https://doi.org/10.48550/arxiv.1704.02801openalex-extracted
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
inferredcites →https://doi.org/10.48550/arxiv.1712.04912openalex-extracted
Quasi-Oracle Estimation of Heterogeneous Treatment Effects
inferredcites →https://doi.org/10.48550/arxiv.1906.02120openalex-extracted
Adapting Neural Networks for the Estimation of Treatment Effects
inferredcites →https://doi.org/10.48550/arxiv.1908.08526openalex-extracted
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes
inferredcites →https://doi.org/10.48550/arxiv.2001.04754openalex-extracted
Learning Overlapping Representations for the Estimation of Individualized Treatment Effects
inferredcites →https://doi.org/10.48550/arxiv.2009.14286openalex-extracted
Benign overfitting in ridge regression
inferredcites →https://doi.org/10.48550/arxiv.2101.10943openalex-extracted
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
inferredcites →https://doi.org/10.48550/arxiv.2105.00416openalex-extracted
Selective Inference in Propensity Score Analysis
inferredcites →https://doi.org/10.48550/arxiv.2106.03765openalex-extracted
On Inductive Biases for Heterogeneous Treatment Effect Estimation
inferredcites →https://doi.org/10.48550/arxiv.2111.12161openalex-extracted
Sensitivity Analysis of Individual Treatment Effects: A Robust Conformal Inference Approach
inferredcites →https://doi.org/10.48550/arxiv.2202.05245openalex-extracted
Benign-Overfitting in Conditional Average Treatment Effect Prediction with Linear Regression
inferredcites →https://doi.org/10.48550/arxiv.2304.07726openalex-extracted
Bayesian Causal Synthesis for Meta-Inference on Heterogeneous Treatment Effects
inferredcites →https://doi.org/10.48550/arxiv.2310.16819openalex-extracted
CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression
inferredcites →https://doi.org/10.48550/arxiv.2403.02467openalex-extracted
Applied Causal Inference Powered by ML and AI
inferredcites →https://doi.org/10.5555/1248547.1248637openalex-extracted
On Model Selection Consistency of Lasso
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Restricted Eigenvalue Properties for Correlated Gaussian Designs
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