no code implementations • 15 Apr 2024 • Razieh Nabi, Nima S. Hejazi, Mark J. Van Der Laan, David Benkeser
Constrained learning has become increasingly important, especially in the realm of algorithmic fairness and machine learning.
1 code implementation • 15 Dec 2023 • Anna Guo, David Benkeser, Razieh Nabi
As an alternative, the front-door criterion offers a solution, even in the presence of unmeasured confounders between treatment and outcome.
1 code implementation • 13 May 2022 • Ziyue Wu, David Benkeser
Super learning, an ensemble method that combines a range of candidate models, is a promising alternative for cost estimation and has shown benefits over a single model.
no code implementations • 16 Jan 2020 • David Benkeser
Understanding the pathways whereby an intervention has an effect on an outcome is a common scientific goal.
no code implementations • 18 Jun 2018 • Cheng Ju, David Benkeser, Mark J. Van Der Laan
Many estimators of the average effect of a treatment on an outcome require estimation of the propensity score, the outcome regression, or both.