Survey Sampling Theory and Applications
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Product details:
- Publisher Elsevier Science
- Date of Publication 9 March 2017
- ISBN 9780128118481
- Binding Paperback
- No. of pages930 pages
- Size 228x152 mm
- Weight 1340 g
- Language English 0
Categories
Long description:
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.
MoreTable of Contents:
1. Preliminaries and Basics of Probability Sampling
2. Unified Sampling Theory: Design-Based Inference
3. Simple Random Sampling
4. Systematic Sampling
5. Unequal Probability Sampling
6. Inference Under Superpopulation Model
7. Stratified Sampling
8. Ratio Method of Estimation
9. Regression, Product, and Calibrated Methods of Estimation
10. Two-Phase Sampling
11. Repetitive Sampling
12. Cluster Sampling
13. Multistage Sampling
14. Variance/Mean Square Estimation
15. Nonsampling Errors
16. Randomized Response Techniques
17. Domain and Small Area Estimation
18. Variance Estimation: Complex Survey Designs
19. Complex Surveys: Categorical Data Analysis
20. Complex Survey Design: Regression Analysis
21. Ranked Set Sampling
22. Estimating Functions
23. Estimation of Distribution Functions and Quantiles
24. Controlled Sampling
25. Empirical Likelihood Method in Survey Sampling
26. Sampling Rare and Mobile Populations
