Nima S. Hejazi | DeepAI

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∙ 04/11/2023

A nonparametric framework for treatment effect modifier discovery in high dimensions

Heterogeneous treatment effects are driven by treatment effect modifiers...

0 Philippe Boileau, et al. ∙

∙ 08/17/2022

Revisiting the propensity score's central role: Towards bridging balance and efficiency in the era of causal machine learning

About forty years ago, in a now–seminal contribution, Rosenbaum Rubi...

0 Nima S. Hejazi, et al. ∙

∙ 05/11/2022

Efficient estimation of modified treatment policy effects based on the generalized propensity score

Continuous treatments have posed a significant challenge for causal infe...

0 Nima S. Hejazi, et al. ∙

∙ 02/07/2022

Causal survival analysis under competing risks using longitudinal modified treatment policies

Longitudinal modified treatment policies (LMTP) have been recently devel...

0 Iván Díaz, et al. ∙

∙ 11/01/2021

A framework for causal segmentation analysis with machine learning in large-scale digital experiments

We present an end-to-end methodological framework for causal segment dis...

0 Nima S. Hejazi, et al. ∙

∙ 09/28/2021

Evaluating the Robustness of Targeted Maximum Likelihood Estimators via Realistic Simulations in Nutrition Intervention Trials

Several recently developed methods have the potential to harness machine...

0 Haodong Li, et al. ∙

∙ 02/19/2021

Cross-Validated Loss-Based Covariance Matrix Estimator Selection in High Dimensions

The covariance matrix plays a fundamental role in many modern explorator...

0 Philippe Boileau, et al. ∙

∙ 09/14/2020

Nonparametric causal mediation analysis for stochastic interventional (in)direct effects

Causal mediation analysis has historically been limited in two important...

0 Nima S. Hejazi, et al. ∙

∙ 06/12/2020

Targeting Learning: Robust Statistics for Reproducible Research

Targeted Learning is a subfield of statistics that unifies advances in c...

3 Jeremy R. Coyle, et al. ∙

∙ 05/22/2020

Nonparametric inverse probability weighted estimators based on the highly adaptive lasso

Inverse probability weighted estimators are the oldest and potentially m...

8 Ashkan Ertefaie, et al. ∙

∙ 03/30/2020

Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials

The advent and subsequent widespread availability of preventive vaccines...

0 Nima S. Hejazi, et al. ∙

∙ 12/20/2019

Non-parametric efficient causal mediation with intermediate confounders

Interventional effects for mediation analysis were proposed as a solutio...

0 Iván Díaz, et al. ∙

∙ 04/24/2017

Data-adaptive statistics for multiple hypothesis testing in high-dimensional settings

Current statistical inference problems in areas like astronomy, genomics...

0 Weixin Cai, et al. ∙

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