1st Edition

Every Coin Has Two Sides An Introduction to Causal Inference in Pharmaceutical Statistics

By Yixin Fang Copyright 2027
392 Pages 8 Color & 27 B/W Illustrations
by Chapman & Hall

Every Coin Has Two Sides: An Introduction to Causal Inference in Pharmaceutical Statistics  introduces basic and advanced statistical inference methods and causal inference methods relevant to pharmaceutical statics. This book distills seventy fundamental ideas and concepts—symbolized as gold coins, each with two sides—essential for mastering asymptotic statistics, causal inference,... Read more

Preface I An Introduction to Asymptotic Statistics 1 The Number Two 2 Fundamentals of Asymptotic Statistics 3 Statistical Inference 4 Maximum Likelihood Estimation (MLE) 5 Minimum Loss Estimation (MLE) II An Introduction to Causal Inference 6 Potential Outcomes 7 Study Designs 8 Estimand 9 Estimator 10 Sensitivity Analysis III An Introduction to Semiparametric Statistics 11 Regular and Asymptotically Linear Estimator 12 Efficient Influence Function 13 A Convenient Approach 14 Missing Data 15 Longitudinal Data IV An Introduction to Targeted Learning 16 Super Learning 17 Targeted Learning 18 Implementation 19 Intercurrent Events 20 Fusion of Two Cultures Bibliography Index

Biography

Yixin Fang is Director of Statistics and Senior 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. He is an elected Fellow of the American Statistical Association.