Biased Sampling, Over-identified Parameter Problems and Beyond
Authors: Qin, Jing
- 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
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- About this book
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This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc.
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. - About the authors
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Dr. Jing Qin currently serves as a Mathematical Statistician at the National Institute of Allergy and Infectious Diseases (NIAID). He received his Ph.D. in Statistics from the University of Waterloo, Canada and completed his postdoctoral studies at Stanford University and the University of Waterloo. His research interests include case-control studies, epidemiology studies, missing data analysis, causal inference, and related applied problems.
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- Download Table of contents PDF (253 KB)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Biased Sampling, Over-identified Parameter Problems and Beyond
- Authors
-
- Jing Qin
- Series Title
- ICSA Book Series in Statistics
- Copyright
- 2017
- Publisher
- Springer Singapore
- Copyright Holder
- Springer Nature Singapore Pte Ltd.
- eBook ISBN
- 978-981-10-4856-2
- DOI
- 10.1007/978-981-10-4856-2
- Hardcover ISBN
- 978-981-10-4854-8
- Series ISSN
- 2199-0980
- Edition Number
- 1
- Number of Pages
- XVI, 624
- Number of Illustrations and Tables
- 4 b/w illustrations, 1 illustrations in colour
- Topics