Inverse probability of exposure & censoring weights | Xiaojuan Li, PhD | Sep 30, 2021

Marginal structural models with inverse probability weighted estimators are increasingly used to estimate causal effects of treatment in nonrandomized studies using real-world data. This presentation will introduce the basics of inverse probability of treatment weight and censoring weights and discuss opportunities and challenges of using these approaches for causal effects of medication use in routinely collected healthcare utilization databases.