Image de couverture de livre

Robust Inference for Mediated Effects in Partially Linear Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Hines, Oliver, Vansteelandt, Stijn, Diaz-Ordaz, Karla
Format:	Preprint
Publié:	2020
Sujets:	Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Optimally weighted average derivative effects
par: Hines, Oliver, et autres
Publié: (2023)

Variable importance measures for heterogeneous treatment effects
par: Hines, Oliver J., et autres
Publié: (2022)

Parameterising the effect of a continuous treatment using average derivative effects
par: Hines, Oliver J., et autres
Publié: (2021)

On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression
par: Dukes, Oliver, et autres
Publié: (2021)

Targeted learning of heterogeneous treatment effect curves for right censored or left truncated time-to-event data
par: Pryce, Matthew, et autres
Publié: (2026)

On Weighted Orthogonal Learners for Heterogeneous Treatment Effects
par: Morzywolek, Pawel, et autres
Publié: (2023)

Robust Covariate Adjustment in Multi-Center Randomized Trials
par: Alene, Muluneh, et autres
Publié: (2025)

Robust evaluation of treatment effects in longitudinal studies with truncation by death or other intercurrent events
par: Baklicharov, Georgi, et autres
Publié: (2025)

Automated, efficient and model-free inference for randomized clinical trials via data-driven covariate adjustment
par: Van Lancker, Kelly, et autres
Publié: (2024)

Chasing Shadows: How Implausible Assumptions Skew Our Understanding of Causal Estimands
par: Vansteelandt, Stijn, et autres
Publié: (2024)

On estimands in target trial emulation
par: Gervasoni, Edoardo Efrem, et autres
Publié: (2026)

Assumption-Lean Quantile Regression
par: Baklicharov, Georgi, et autres
Publié: (2024)

Causal machine learning methods and use of cross-fitting in settings with high-dimensional confounding
par: Ellul, Susan, et autres
Publié: (2024)

Two Stage Least Squares with Time-Varying Instruments: An Application to an Evaluation of Treatment Intensification for Type-2 Diabetes
par: Tompsett, Daniel, et autres
Publié: (2024)

Causal machine learning for high-dimensional mediation analysis using interventional effects mapped to a target trial
par: Chen, Tong, et autres
Publié: (2025)

Integration of aggregated data in causally interpretable meta-analysis by inverse weighting
par: Vo, Tat-Thang, et autres
Publié: (2025)

Automatic debiasing of neural networks via moment-constrained learning
par: Hines, Christian L., et autres
Publié: (2024)

Instrumental Variable methods to target Hypothetical Estimands with longitudinal repeated measures data: Application to the STEP 1 trial
par: Bowden, Jack, et autres
Publié: (2024)

PLRD: Partially Linear Regression Discontinuity Inference
par: Ghosh, Aditya, et autres
Publié: (2025)

Robust Inference for High-dimensional Linear Models with Heavy-tailed Errors via Partial Gini Covariance
par: Zhang, Yilin, et autres
Publié: (2024)

Causal-ICM: A Data Fusion Framework For Heterogeneous Treatment Effect Estimation With Multi-Task Gaussian Processes
par: Dimitriou, Evangelos, et autres
Publié: (2024)

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

The Probability of Tiered Benefit: Partial Identification with Robust and Stable Inference
par: de Aguas, Johan, et autres
Publié: (2025)

Explainable AI for survival analysis: a median-SHAP approach
par: Ter-Minassian, Lucile, et autres
Publié: (2024)

Robust Inference for Causal Mediation Analysis of Recurrent Event Data
par: Chen, Yan-Lin, et autres
Publié: (2023)

Model-Robust Direct Effect Under Confounder-Mediator Ambiguity
par: Ghassami, AmirEmad
Publié: (2026)

Robust Inference for Generalized Linear Mixed Models: An Approach Based on Score Sign Flipping
par: Andreella, Angela, et autres
Publié: (2024)

Causal machine learning for heterogeneous treatment effects in the presence of missing outcome data
par: Pryce, Matthew, et autres
Publié: (2024)

The super learner for time-to-event outcomes: A tutorial
par: Keogh, Ruth H., et autres
Publié: (2025)

Propensity weighting plus adjustment in proportional hazards model is not doubly robust
par: Gabriel, Erin E, et autres
Publié: (2023)

Perturbation-Robust Predictive Modeling of Social Effects by Network Subspace Generalized Linear Models
par: Wang, Jianxiang, et autres
Publié: (2024)

Robust Inference for Non-Linear Regression Models with Applications in Enzyme Kinetics
par: Jana, Suryasis, et autres
Publié: (2024)

Robust Estimation and Model Selection for the Controlled Directed Effect with Unmeasured Mediator-Outcome Confounders
par: Orihara, Shunichiro, et autres
Publié: (2024)

Constrained Design of a Binary Instrument in a Partially Linear Model
par: Morrison, Tim, et autres
Publié: (2024)

Targeted Learning on Variable Importance Measure for Heterogeneous Treatment Effect
par: Li, Haodong, et autres
Publié: (2023)

Robust Universal Inference For Misspecified Models
par: Park, Beomjo, et autres
Publié: (2023)

Block Empirical Likelihood Inference for Longitudinal Generalized Partially Linear Single-Index Models
par: Zhang, Tianni, et autres
Publié: (2026)

Inference on the Significance of Modalities in Multimodal Generalized Linear Models
par: Jin, Wanting, et autres
Publié: (2026)

Causal Inference in Randomized Trials with Partial Clustering
par: Nugent, Joshua, et autres
Publié: (2024)

Residual-based Alternative Partial Least Squares for Generalized Functional Linear Models
par: Wang, Yue, et autres
Publié: (2025)