An Introduction to Model-Based Survey Sampling with Applications

Hardcover | February 15, 2012

byRay Chambers, Robert Clark

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This text brings together important ideas on the model-based approach to sample survey, which has been developed over the last twenty years. Suitable for graduate students and professional statisticians, it moves from basic ideas fundamental to sampling to more rigorous mathematical modellingand data analysis and includes exercises and solutions.

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This text brings together important ideas on the model-based approach to sample survey, which has been developed over the last twenty years. Suitable for graduate students and professional statisticians, it moves from basic ideas fundamental to sampling to more rigorous mathematical modellingand data analysis and includes exercises an...

Ray Chambers is a Professor in the School of Mathematics and Applied Statistics at the University of Wollongong, Australia, and Robert Clark is alos a Professor in the School of Mathematics and Applied Statistics at the University of Wollongong, Australia.

other books by Ray Chambers

Format:HardcoverDimensions:352 pages, 9.21 × 6.14 × 0.1 inPublished:February 15, 2012Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:019856662X

ISBN - 13:9780198566625

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Table of Contents

Part I: Basics of Model-Based Survey Inference1. Introduction2. The Model-Based Approach3. Homogeneous Populations4. Stratified Populations5. Populations with Regression Structure6. Clustered Populations7. The General Linear Population ModelPart II: Robust Model-Based Inference8. Robust Prediction under Model Misspecification9. Robust Estimation of the Prediction Variance10. Outlier Robust PredictionPart III: Applications of Model-Based Survey Inference11. Inference for Nonlinear Population Parameters12. Survey Inference via Sub-Sampling13. Estimation for Multipurpose Surveys14. Inference for Domains15. Prediction for Small Areas16. Model-Based Inference for Distributions and Quantiles17. Using Transformations in Sample Survey InferenceExercises