Biased Sampling, Over-identified Parameter Problems and Beyond

By:

Jing Qin

Format:

Paperback / softback

Series:

ICSA Book Series in Statistics

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Description

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.

Author Biography:

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.

Release date Australia

December 9th, 2018

Author

Jing Qin

Audience

Professional & Vocational

Edition

Softcover reprint of the original 1st ed. 2017

Illustrations

1 Illustrations, color; 4 Illustrations, black and white; XVI, 624 p. 5 illus., 1 illus. in color.

Pages

624

Series

ICSA Book Series in Statistics

ISBN-13

9789811352492

Product ID

28998372

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