Cover Image

A scalable Bayesian double machine learning framework for high dimensional causal estimation, with application to racial disproportionality assessment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Luo, Yu, McNealis, Vanessa, Li, Yijing
Format:	Preprint
Published:	2025
Subjects:	Applications Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Smoothed pseudo-population bootstrap methods with applications to finite population quantiles
by: McNealis, Vanessa, et al.
Published: (2024)

A longitudinal Bayesian framework for estimating causal dose-response relationships
by: Luo, Yu, et al.
Published: (2025)

Plasmode simulation for the evaluation of causal inference methods in homophilous social networks
by: McNealis, Vanessa, et al.
Published: (2024)

Joint mixed-effects models for causal inference in clustered network-based observational studies
by: McNealis, Vanessa, et al.
Published: (2024)

Robust Bayesian causal estimation for causal inference in medical diagnosis
by: Basu, Tathagata, et al.
Published: (2024)

Revisiting the Effects of Maternal Education on Adolescents' Academic Performance: Doubly Robust Estimation in a Network-Based Observational Study
by: McNealis, Vanessa, et al.
Published: (2023)

Double machine learning to estimate the effects of multiple treatments and their interactions
by: Xiang, Qingyan, et al.
Published: (2025)

Multiply robust estimation for causal survival analysis with treatment noncompliance
by: Cheng, Chao, et al.
Published: (2023)

A scalable two-stage Bayesian approach accounting for exposure measurement error in environmental epidemiology
by: Lee, Changwoo J., et al.
Published: (2024)

crumble: A comprehensive framework for modern causal mediation analysis with intermediate confounding
by: Liu, Richard, et al.
Published: (2026)

A Bayesian semi-parametric approach to causal mediation for longitudinal mediators and time-to-event outcomes with application to a cardiovascular disease cohort study
by: Bhandari, Saurabh, et al.
Published: (2024)

Bayesian nonparametric mixtures of categorical directed graphs for heterogeneous causal inference
by: Castelletti, Federico, et al.
Published: (2024)

A Bayesian theory for estimation of biodiversity
by: Rigon, Tommaso, et al.
Published: (2025)

Pulling back the curtain: the road from statistical estimand to machine-learning based estimator for epidemiologists (no wizard required)
by: Renson, Audrey, et al.
Published: (2025)

Comparing causal parameters with many treatments and positivity violations
by: McClean, Alec, et al.
Published: (2024)

Sharp variance estimator and causal bootstrap in stratified randomized experiments
by: Yu, Haoyang, et al.
Published: (2024)

Bayesian kernel machine regression for heteroscedastic health outcome data
by: Smith, Melissa J., et al.
Published: (2025)

A Bayesian framework for measuring association and its application to emotional dynamics in Web discourse
by: Xavier, Henrique S., et al.
Published: (2023)

Handling missing data when estimating causal effects with Targeted Maximum Likelihood Estimation
by: Dashti, S. Ghazaleh, et al.
Published: (2021)

Autoregressive models for panel data causal inference with application to state-level opioid policies
by: Antonelli, Joseph, et al.
Published: (2024)

A continuous-time Markov chain framework for population size estimation from multi-list data: accounting for absorbing lists and asymmetric interactions
by: Schaller, Ophélie, et al.
Published: (2026)

A Bayesian hierarchical mixture cure modelling framework to utilize multiple survival datasets for long-term survivorship estimates: A case study from previously untreated metastatic melanoma
by: Green, Nathan, et al.
Published: (2024)

Bayesian estimation of clustered dependence structures in functional neuroconnectivity
by: Kim, Hyoshin, et al.
Published: (2023)

Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes
by: Liu, Xueqing, et al.
Published: (2023)

Assessing variable importance in survival analysis using machine learning
by: Wolock, Charles J., et al.
Published: (2023)

A statistical framework for dynamic cognitive diagnosis in digital learning environments
by: Ma, Yawen, et al.
Published: (2025)

A Bayesian hierarchical framework for fusion of remote sensing data: An example with solar-induced fluorescence
by: Johny, Manju, et al.
Published: (2025)

Sparse covariate-driven factorization of high-dimensional brain connectivity with application to site effect correction
by: Zhang, Rongqian, et al.
Published: (2026)

Quantifying uncertainty of individualized treatment effects in right-censored survival data: A comparison of Bayesian additive regression trees and causal survival forest
by: Kabata, Daijiro, et al.
Published: (2025)

A Bayesian modelling framework for health care resource use and costs in trial-based economic evaluations
by: Gabrio, Andrea
Published: (2024)

A tree-based kernel for densities and its applications in clustering DNase-seq profiles
by: Xu, Yuliang, et al.
Published: (2025)

A machine learning approach based on survival analysis for IBNR frequencies in non-life reserving
by: Hiabu, Munir, et al.
Published: (2023)

DiPPER: A Bayesian approach to differential prevalence analysis with applications in microbiome studies
by: Pelto, Juho, et al.
Published: (2026)

Multivariate lattice deformation: A spatially explicit framework for assessing crop rotation impacts on soil nutrient dynamics
by: Mandap, Marco
Published: (2026)

Feature aware covariance estimation, with application to mixtures of chemical exposures
by: Bersson, Elizabeth, et al.
Published: (2025)

Bayesian nonparametric clustering for spatio-temporal data, with an application to air pollution
by: Aiello, Luca, et al.
Published: (2025)

A Bayesian block maxima over threshold approach applied to corrosion assessment in heat exchanger tubes
by: Spearing, Jess, et al.
Published: (2025)

Flexible Bayesian Tensor Decomposition for Verbal Autopsy Data
by: Zhu, Yu, et al.
Published: (2025)

High-dimensional Bayesian Model for Disease-Specific Gene Detection in Spatial Transcriptomics
by: Zhao, Qicheng, et al.
Published: (2024)

Risk-Adjusted learning curve assessment using comparative probability metrics
by: Nadi, Adel Ahmadi, et al.
Published: (2025)