Trusting the Untestable: Validation and Diagnostics for the Doubly Robust Models

Lyft's data science team developed validation methods for Augmented Inverse Propensity Weighting (AIPW), a doubly robust causal inference model used when A/B testing isn't feasible. The platform requires rigorous confounder management with hundreds of features, applies propensity score corrections for downsampled data, and Show more