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

The book introduces basic and advanced statistical inference and causal inference methods relevant to pharmaceutical statics and distills seventy fundamental ideas and concepts—symbolized as gold coins, each with two sides—essential for mastering asymptotic statistics, causal inference, semiparametric statistics, and targeted learning.

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 statistics. This book distills seventy fundamental ideas and concepts—symbolized as gold coins, each with two sides—essential for mastering asymptotic statistics, causal inference, semiparametric statistics, and targeted learning. This book covers causal thinking that has increasingly become important in the planning, design, conduct, analysis, and interpretation of clinical studies. Progressing from basic statistical concepts to advanced targeted learning techniques, the book highlights the fusion of two cultures of statistical modelling. This book is suitable for graduate students in statistics, biostatistics, public health, and data science who are looking to pursue a career in the pharmaceutical industry, as well as for clinical statisticians and epidemiologists working in the pharmaceutical industry. Key Features:Causal inference book for clinical statisticians in the pharmaceutical industry and graduate studentsIntroduction to asymptotic statistics, causal inference, semiparametric statistics, and targeted learningAligning with FDA and ICH guidance documents and covering different stages of clinical studies Seventy fundamental ideas and concepts—symbolized as gold coins, each with two sides