Yixin Fang, Ph.D. is Director of Statistics and Research Fellow at AbbVie Inc. He obtained his Ph.D. in Statistics from Columbia University and is an experienced statistician and data scientist who has a history of working in both the biopharmaceutical industry and academia.

"This book can serve as a reference for experienced statisticians interested in extending their research to semiparametric efficiency theory and incorporating machine learning approaches into their causal methodology, as well as an introductory resource for graduate students in statistics, bio-statistics, or data science interested in causal inference and applications to pharmacy."-Ashley L. Buchanan in the Journal of the American Statistical Association, July 2025.

• Preface1. Introduction2. Randomized Controlled Clinical Trials3. Missing Data Handling4. Intercurrent Events Handling5. Longitudinal Studies6. Real-World Evidence Studies7. The Art of Estimation (I): M-estimation8. The Art of Estimation (II): TMLE9. The Art of Estimation (III): LTMLE10. Sensitivity Analysis11. A Roadmap for Causal Inference12. Applications of the RoadmapBibliography

Yixin Fang, Ph.D. is Director of Statistics and Research Fellow at AbbVie Inc. He obtained his Ph.D. in Statistics from Columbia University and is an experienced statistician and data scientist who has a history of working in both the biopharmaceutical industry and academia.

"This book can serve as a reference for experienced statisticians interested in extending their research to semiparametric efficiency theory and incorporating machine learning approaches into their causal methodology, as well as an introductory resource for graduate students in statistics, bio-statistics, or data science interested in causal inference and applications to pharmacy."-Ashley L. Buchanan in the Journal of the American Statistical Association, July 2025.

• Preface1. Introduction2. Randomized Controlled Clinical Trials3. Missing Data Handling4. Intercurrent Events Handling5. Longitudinal Studies6. Real-World Evidence Studies7. The Art of Estimation (I): M-estimation8. The Art of Estimation (II): TMLE9. The Art of Estimation (III): LTMLE10. Sensitivity Analysis11. A Roadmap for Causal Inference12. Applications of the RoadmapBibliography

Yixin Fang, Ph.D. is Director of Statistics and Research Fellow at AbbVie Inc. He obtained his Ph.D. in Statistics from Columbia University and is an experienced statistician and data scientist who has a history of working in both the biopharmaceutical industry and academia.

"This book can serve as a reference for experienced statisticians interested in extending their research to semiparametric efficiency theory and incorporating machine learning approaches into their causal methodology, as well as an introductory resource for graduate students in statistics, bio-statistics, or data science interested in causal inference and applications to pharmacy."-Ashley L. Buchanan in the Journal of the American Statistical Association, July 2025.

• Preface1. Introduction2. Randomized Controlled Clinical Trials3. Missing Data Handling4. Intercurrent Events Handling5. Longitudinal Studies6. Real-World Evidence Studies7. The Art of Estimation (I): M-estimation8. The Art of Estimation (II): TMLE9. The Art of Estimation (III): LTMLE10. Sensitivity Analysis11. A Roadmap for Causal Inference12. Applications of the RoadmapBibliography