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Biased Sampling, Over-identified Parameter Problems and Beyond (ICSA Book Series in Statistics) - Softcover
Synopsis
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.
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About the Author
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.
Review
“This book is the first comprehensive overview of which I am aware that shows how statistical methods such as empirical likelihood and generalized method of moments can be appropriately and efficiently used in the over-identified parameter problem. ... With its extensive exercises and easy style, this book is suitable as an upper-level textbook for graduate students or as a reference book for workshops that target postdoctoral fellows and junior researchers.” (JingNing, Journal of the American Statistical Association JASA, Vol. 113 (522), 2018)
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- PublisherSpringer
- Publication date2018
- ISBN 10 9811352496
- ISBN 13 9789811352492
- BindingPaperback
- LanguageEnglish
- Number of pages640
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 640 pp. Englisch. Seller Inventory # 9789811352492
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