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© 2019

Analysis of Doubly Truncated Data

An Introduction

Book

Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Also part of the JSS Research Series in Statistics book sub series (JSSRES)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Achim Dörre, Takeshi Emura
    Pages 1-18
  3. Achim Dörre, Takeshi Emura
    Pages 19-40
  4. Achim Dörre, Takeshi Emura
    Pages 41-62
  5. Achim Dörre, Takeshi Emura
    Pages 63-74
  6. Achim Dörre, Takeshi Emura
    Pages 75-86
  7. Back Matter
    Pages 87-109

About this book

Introduction

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.

Keywords

Survival Analysis Left-truncation Double-truncation Lifetime Distribution Biased Sampling Exponential Family Maximum Likelihood Estimation

Authors and affiliations

  1. 1.Department of EconomicsUniversity of RostockRostockGermany
  2. 2.Graduate Institute of StatisticsNational Central UniversityTaoyuan CityTaiwan

About the authors

Achim Dörre, University of Rostock

 

Takeshi Emura, Chang Gung University


Bibliographic information

Reviews

“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)