Authors:
- Provides a comprehensive overview of traditional statistical methods such as likelihood based inference and estimating function theory
- Extensively discusses many different biased sampling problems
- Explicitly addresses the connections between Godambe’s estimating function theory, Hansen’s generalized method of moments, and Qin and Lawless’ empirical likelihood approach for over-identified parameter problems
- Makes the general theory of biased sampling accessible to upper undergraduate and graduate students
- Includes supplementary material: sn.pub/extras
- Includes supplementary material: sn.pub/extras
Part of the book series: ICSA Book Series in Statistics (ICSABSS)
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Table of contents (26 chapters)
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Front Matter
About this book
The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others.
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Authors and Affiliations
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Biostatistics Research Branch, National Institute of Allergy and Infect Biostatistics Research Branch, Bethesda, USA
Jing Qin
About the author
Bibliographic Information
Book Title: Biased Sampling, Over-identified Parameter Problems and Beyond
Authors: Jing Qin
Series Title: ICSA Book Series in Statistics
DOI: https://doi.org/10.1007/978-981-10-4856-2
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2017
Hardcover ISBN: 978-981-10-4854-8Published: 29 June 2017
Softcover ISBN: 978-981-13-5249-2Published: 09 December 2018
eBook ISBN: 978-981-10-4856-2Published: 14 June 2017
Series ISSN: 2199-0980
Series E-ISSN: 2199-0999
Edition Number: 1
Number of Pages: XVI, 624
Number of Illustrations: 4 b/w illustrations, 1 illustrations in colour
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Applications of Mathematics, Economic Theory/Quantitative Economics/Mathematical Methods