Robust Weighted Triangulation of Causal Effects Under Model Uncertainty

Researchers developed a new framework for causal effect triangulation that combines multiple statistical models to improve causal inference from observational data. The method addresses model uncertainty by using data-driven measures of model validity without requiring commitment to a single specification.