Advanced Causal Inference Framework

Project Overview

This project involves building a comprehensive causal inference framework that goes beyond traditional A/B testing to measure true incremental impact of marketing campaigns. The framework implements advanced econometric techniques including propensity score matching, instrumental variables, and regression discontinuity designs to establish causality in complex business environments.

Key Features

• Advanced causal inference methods beyond A/B testing
• Propensity score matching for observational studies
• Instrumental variables for natural experiments
• Regression discontinuity for threshold-based analysis
• Heterogeneous treatment effect estimation
• Automated causal graph construction and validation