Can we train machine learning methods to outperform the high-dimensional propensity score algorithm?

Can we train machine learning methods to outperform the high-dimensional propensity score algorithm?

Overview

Description

This study compares covariate selection strategies for confounding adjustment in secondary database analyses via Plasmode simulation: high-dimensional propensity score, machine learning algorithms: lasso, elastic net, random forest, etc.

Manuscripts

Presentations

Project Team

Corresponding Author
Collaborator
Robert W. Platt PhD
Collaborator
Menglan Pang MSc