Comparative Evaluation of Automated Approaches for Confounder Selection in High-Dimensional Data with Rare Outcomes

​​​​​This presentation explores the performance of several lasso-based methods for large-scale confounder selection in ultra high-dimensional data with rare outcomes using simulated datasets. It was presented at the 38th International Conference on Pharmacoepidemiology and Therapeutic Risk Management.