Biased Sampling, Over-identified Parameter Problems and Beyond

  • Jing Qin

Part of the ICSA Book Series in Statistics book series (ICSABSS)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Jing Qin
    Pages 85-110
  3. Jing Qin
    Pages 129-138
  4. Jing Qin
    Pages 249-257
  5. Jing Qin
    Pages 409-425
  6. Jing Qin
    Pages 447-466
  7. Jing Qin
    Pages 477-518
  8. Back Matter
    Pages 601-624

About this book


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. 


Biased Sampling Problems Finite Mixture Models Genetic Epidemiology Parametric Likelihood Survey Sampling

Authors and affiliations

  • Jing Qin
    • 1
  1. 1.Biostatistics Research BranchNational Institute of Allergy and Infect Biostatistics Research BranchBethesdaUSA

Bibliographic information

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