Description:
This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields.
Review Quotes:
"The aim of this book is to provide some fundamental ideas and methodologies for analysing doubly truncated data. ... The methodology of this book could be helpful to avoid a systematic bias in the contents of data due to loss of information." (Nikita E. Ratanov, zbMATH 1434.62008, 2020)