Survey Sampling Theory and Applications

Häftad, Engelska, 2017

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Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling.

The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students.

Covers a wide spectrum of topics on survey sampling and statistics
Serves as an ideal text for graduate students and researchers in survey sampling theory and applications
Contains material on recent developments in survey sampling not covered in other books
Illustrates theories using numerical examples and exercises

Produktinformation

Utgivningsdatum2017-03-09
Mått152 x 229 x undefined mm
Vikt1 340 g
FormatHäftad
SpråkEngelska
Antal sidor930
FörlagElsevier Science
ISBN9780128118481

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Prof. Raghunath Arnab is a Professor of Statistics, University of Botswana, Botswana and Honorary Professor of Statistics, University of KwaZulu-Natal, South Africa. Prof. Arnab received his Ph.D. degree in 1981 from the Indian Statistical Institute, Kolkata. He is a co-author of the book A new concept for tuning design weights in survey sampling (jointly with Prof. S. Singh, Prof. A. Sedory, Prof. M. der Mar Rueda, Prof. A. Arcos) and an author of numerous research articles, Associate editor of the Journal of Statistical Theory and Practice, Model Assisted statistics and its Applications, Journal of the Indian Society of Agricultural Statistics and Advances and Applications in Statistics. Prof. Arnab was an elected member of the International Statistical Institute, Life member of the International Statistical Institute and a member of the Biometric Society.

1. Preliminaries and Basics of Probability Sampling2. Unified Sampling Theory: Design-Based Inference3. Simple Random Sampling4. Systematic Sampling5. Unequal Probability Sampling6. Inference Under Superpopulation Model7. Stratified Sampling8. Ratio Method of Estimation9. Regression, Product, and Calibrated Methods of Estimation10. Two-Phase Sampling11. Repetitive Sampling12. Cluster Sampling13. Multistage Sampling14. Variance/Mean Square Estimation15. Nonsampling Errors16. Randomized Response Techniques17. Domain and Small Area Estimation18. Variance Estimation: Complex Survey Designs19. Complex Surveys: Categorical Data Analysis20. Complex Survey Design: Regression Analysis21. Ranked Set Sampling22. Estimating Functions23. Estimation of Distribution Functions and Quantiles24. Controlled Sampling25. Empirical Likelihood Method in Survey Sampling26. Sampling Rare and Mobile Populations