Many observational studies in epidemiology and other disciplines face inherent limitations in study design and data quality, such as selection bias, unobserved variables, and poorly measured variables. Accessible to statisticians and researchers from various disciplines, this book presents an overview of Bayesian inference in partially identified models. It includes many examples to illustrate the methods and provides R code for their implementation on the book’s website. The author also addresses a number of open questions to stimulate further research in this area.
