Analysis of Doubly Truncated Data: An Introduction

Author:   Achim Dörre ,  Takeshi Emura
Publisher:   Springer Verlag, Singapore
Edition:   1st ed. 2019
ISBN:  

9789811362408


Pages:   109
Publication Date:   22 May 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Analysis of Doubly Truncated Data: An Introduction


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Overview

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.

Full Product Details

Author:   Achim Dörre ,  Takeshi Emura
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   1st ed. 2019
Weight:   0.454kg
ISBN:  

9789811362408


ISBN 10:   9811362408
Pages:   109
Publication Date:   22 May 2019
Audience:   College/higher education ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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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)


“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)


Author Information

Achim Dörre, University of Rostock   Takeshi Emura, Chang Gung University

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