Biased Sampling, Over-identified Parameter Problems and Beyond

Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics, Applied
Cover of the book Biased Sampling, Over-identified Parameter Problems and Beyond by Jing Qin, Springer Singapore
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Author: Jing Qin ISBN: 9789811048562
Publisher: Springer Singapore Publication: June 14, 2017
Imprint: Springer Language: English
Author: Jing Qin
ISBN: 9789811048562
Publisher: Springer Singapore
Publication: June 14, 2017
Imprint: Springer
Language: English

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. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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