Analysis of Doubly Truncated Data: An Introduction

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. Front Matter ....Pages i-xvi Introduction to Double-Truncation (Achim Dörre, Takeshi Emura)....Pages 1-18 Parametric Estimation Under Exponential Family (Achim Dörre, Takeshi Emura)....Pages 19-40 Bayesian Inference for Doubly Truncated Data (Achim Dörre, Takeshi Emura)....Pages 41-62 Nonparametric Inference for Double-Truncation (Achim Dörre, Takeshi Emura)....Pages 63-74 Linear Regression Under Random Double-Truncation (Achim Dörre, Takeshi Emura)....Pages 75-86 Back Matter ....Pages 87-109