Main description:

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 modelling and data analysis and includes exercises and solutions.

Contents:

PART I: BASICS OF MODEL-BASED SURVEY INFERENCE ; 1. Introduction ; 2. The Model-Based Approach ; 3. Homogeneous Populations ; 4. Stratified Populations ; 5. Populations with Regression Structure ; 6. Clustered Populations ; 7. The General Linear Population Model ; PART II: ROBUST MODEL-BASED INFERENCE ; 8. Robust Prediction under Model Misspecification ; 9. Robust Estimation of the Prediction Variance ; 10. Outlier Robust Prediction ; PART III: APPLICATIONS OF MODEL-BASED SURVEY INFERENCE ; 11. Inference for Nonlinear Population Parameters ; 12. Survey Inference via Sub-Sampling ; 13. Estimation for Multipurpose Surveys ; 14. Inference for Domains ; 15. Prediction for Small Areas ; 16. Model-Based Inference for Distributions and Quantiles ; 17. Using Transformations in Sample Survey Inference ; Exercises