On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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9 results for “g-formula”

A flexible Bayesian g-formula for causal survival analyses with time-dependent confoundingstat.ME

Developed a flexible Bayesian g-formula for causal survival analysis with time-dependent confounding.

problem Estimating causal survival curves in longitudinal observational studies with time-varying treatments and confounding.

method Incorporated Bayesian Additive Regression Trees (BART) into the g-formula to model time-evolving generative components and mitigate bias due to model misspecification.

result Demonstrated improved empirical performance and practical utility of the proposed method through simulations and real-world data analysis.

Bayesian g-formula causal survival analysis time-dependent confounding time-varying treatments Bayesian Additive Regression Trees (BART)

2024-02-04abs ↗pdf ↗

Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Datastat.ML

Deep learning improves causal effect estimation from complex observational data.

problem Estimating causal effects from complex observational data with low bias.

method Unified deep learning framework using multitask recurrent neural networks.

result Deep learning estimator shows lower bias in causal effect estimates.

deep learning g-formula causal inference observational data non-iterative

2024-10-28abs ↗pdf ↗

Causal Inference with the Napkin Graphstat.ME

A new causal graph framework identifies treatment effects without adjusting for confounders.

problem Invalid identification of causal effects due to unmeasured confounders.

method Developed the Napkin graph to identify causal effects through a ratio of g-formulas, using influence-function-based estimators.

result Demonstrated substantial efficiency gains in estimating causal effects using the Napkin graph.

Causal inference Napkin graph g-formula Verma constraint Efficiency bounds

2025-12-22abs ↗pdf ↗

Causal Interaction Trees: Tree-Based Subgroup Identification for Observational Datastat.ME

Causal Interaction Trees identify treatment subgroup effects in observational data.

problem Identifying subgroups with enhanced treatment effects in observational studies.

method Extending Classification and Regression Trees with subgroup-specific treatment effect estimators.

result The proposed algorithms enhance treatment effect heterogeneity in subgroups.

Causal inference Observational studies Subgroup analysis Treatment effect Tree-based methods

2020-03-06abs ↗pdf ↗

Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysisstat.ML

New approach estimates treatment effects from decentralized data.

problem Estimating treatment effects from multiple studies with limited data.

method Three classes of ATE estimators derived from Plug-in G-Formula.

result Asymptotic variance of estimators for linear models derived.

Federated Causal Inference ATE Estimators Meta-Analysis Randomized Controlled Trials Asymptotic Variance

2024-10-22abs ↗pdf ↗

A Causal Framework for Evaluating ICU Discharge Strategiesstat.ME

The paper tackles ICU discharge strategies by evaluating optimal stopping scenarios.

problem Optimal stopping in ICU discharge with complex causal inference challenges.

method Generalized g-formula implementation and application to MIMIC-IV dataset.

result Improved ICU discharge strategies demonstrated with the g-formula approach.

ICU discharge optimal stopping causal inference MIMIC-IV Python package

2026-03-26abs ↗pdf ↗

Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curvesstat.ME

Proposes estimators for complex dose-response curves using kernel methods.

problem Estimating complex dose-response curves with continuous treatments, mediators, and covariates.

method Kernel ridge regression with sequential kernel embedding technique.

result Simple estimators for mediated and time-varying dose response curves with nonasymptotic uniform rates.

kernel ridge regression mediation analysis time-varying effects nonparametric estimation feedback mechanisms

2021-11-06abs ↗pdf ↗

Model Agnostic Differentially Private Causal Inferencecs.LG

A framework for private causal effect estimation without structural assumptions.

problem Estimating causal effects from private observational data.

method Model-agnostic framework that privatizes predictions and aggregation steps.

result Maintains competitive performance under realistic privacy budgets.

differential privacy causal inference observational studies private statistics

2025-05-26abs ↗pdf ↗

Average Causal Effect Estimation in DAGs with Hidden Variables: Beyond Back-Door and Front-Door Criteriastat.ME

New estimators for causal effects in DAGs with hidden variables, addressing computational and statistical challenges.

problem Estimating causal effects in DAGs with hidden variables beyond traditional criteria.

method Introduces novel one-step corrected plug-in and targeted minimum loss-based estimators for causal effects in DAGs with hidden variables.

result Root-n consistent causal effect estimates with desirable statistical properties.

causal inference hidden variables DAGs machine learning double robustness

2024-09-06abs ↗pdf ↗