Image de couverture de livre

Causal Inference with High-Dimensional Treatments

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kramer, Patrick, Kennedy, Edward H., Opper, Isaac M.
Format:	Preprint
Publié:	2026
Sujets:	Statistics Theory Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Causal Inference with High-dimensional Discrete Covariates
par: Zeng, Zhenghao, et autres
Publié: (2024)

Causal Effect Estimation after Propensity Score Trimming with Continuous Treatments
par: Branson, Zach, et autres
Publié: (2023)

Doubly-Robust Functional Average Treatment Effect Estimation
par: Testa, Lorenzo, et autres
Publié: (2025)

Robust Max Statistics for High-Dimensional Inference
par: Liu, Mingshuo, et autres
Publié: (2024)

On the Equivalence between Neyman Orthogonality and Pathwise Differentiability
par: Chen, Yuxi, et autres
Publié: (2026)

Incremental effects for continuous exposures
par: Schindl, Kyle, et autres
Publié: (2024)

Statistical Inference on High Dimensional Gaussian Graphical Regression Models
par: Meng, Xuran, et autres
Publié: (2024)

Frequency Domain Statistical Inference for High-Dimensional Time Series
par: Krampe, Jonas, et autres
Publié: (2022)

Distribution-uniform anytime-valid sequential inference and the Robbins-Siegmund distributions
par: Waudby-Smith, Ian, et autres
Publié: (2023)

High-Dimensional Single-Index Models: Link Estimation and Marginal Inference
par: Sawaya, Kazuma, et autres
Publié: (2024)

Causal Effect of Functional Treatment
par: Tan, Ruoxu, et autres
Publié: (2022)

Simultaneous Inference in Multiple Matrix-Variate Graphs for High-Dimensional Neural Recordings
par: Liu, Zongge, et autres
Publié: (2024)

Debiased Inference for High-Dimensional Regression Models Based on Profile M-Estimation
par: Wang, Yi, et autres
Publié: (2025)

Efficient Difference-in-Differences Estimation when Outcomes are Missing at Random
par: Testa, Lorenzo, et autres
Publié: (2025)

Causal Inference on Process Graphs, Part II: Causal Structure and Effect Identification
par: Reiter, Nicolas-Domenic, et autres
Publié: (2024)

Minimax Rate-Optimal Inference for Individualized Quantile Treatment Effects in High-dimensional Models
par: Sun, Jiachen, et autres
Publié: (2025)

Double-Estimation-Friendly Inference for High-Dimensional Measurement Error Models with Non-Sparse Adaptability
par: Cui, Shijie, et autres
Publié: (2024)

Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders
par: Wang, Yuhao, et autres
Publié: (2020)

SOFARI: High-Dimensional Manifold-Based Inference
par: Zheng, Zemin, et autres
Publié: (2023)

Statistical Inference for High-Dimensional Robust Linear Regression Models via Recursive Online-Score Estimation
par: Zheng, Dian, et autres
Publié: (2025)

Valid Bayesian Inference based on Variance Weighted Projection for High-Dimensional Logistic Regression with Binary Covariates
par: Ojha, Abhishek, et autres
Publié: (2024)

The Fundamental Limits of Structure-Agnostic Functional Estimation
par: Balakrishnan, Sivaraman, et autres
Publié: (2023)

Stochastic interventions, sensitivity analysis, and optimal transport
par: Levis, Alexander W., et autres
Publié: (2024)

Estimation and Inference for the Average Treatment Effect in a Score-Explained Heterogeneous Treatment Effect Model
par: Wibisono, Kevin Christian, et autres
Publié: (2025)

Estimation and Inference in Ultrahigh Dimensional Partially Linear Single-Index Models
par: Cui, Shijie, et autres
Publié: (2024)

Neyman Jackknife: Design-Based Variance Estimation for Causal Inference under Interference
par: Park, Bryan, et autres
Publié: (2026)

Causal Inference in Biomedical Imaging via Functional Linear Structural Equation Models
par: Li, Ting, et autres
Publié: (2026)

Anytime-Valid Linear Models and Regression Adjusted Causal Inference in Randomized Experiments
par: Lindon, Michael, et autres
Publié: (2022)

Causal Inference on Process Graphs, Part I: The Structural Equation Process Representation
par: Reiter, Nicolas-Domenic, et autres
Publié: (2023)

Semiparametric Causal Inference for Right-Censored Outcomes with Many Weak Invalid Instruments
par: Bu, Qiushi, et autres
Publié: (2025)

Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
par: Sert, Gözde, et autres
Publié: (2025)

Covariance Regression with High-Dimensional Predictors
par: He, Yuheng, et autres
Publié: (2024)

Causal Inference in Longitudinal Data under Unknown Interference
par: Wang, Ye, et autres
Publié: (2021)

Partial Identification of Causal Effects for Endogenous Continuous Treatments
par: Dalal, Abhinandan, et autres
Publié: (2025)

Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters
par: Dalal, Abhinandan, et autres
Publié: (2024)

GMM with Many Weak Moment Conditions and Nuisance Parameters: General Theory and Applications to Causal Inference
par: Wang, Rui, et autres
Publié: (2025)

On Statistical Inference for High-Dimensional Binary Time Series
par: Dai, Dehao, et autres
Publié: (2025)

Efficient High-Dimensional Conditional Independence Testing
par: Banerjee, Bilol
Publié: (2025)

Testing Separability of High-Dimensional Covariance Matrices
par: Sung, Bongjung, et autres
Publié: (2025)

Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference
par: Kato, Masahiro
Publié: (2025)