An Introduction to Model-Based Survey Sampling with Applications

• Excellent exposition on model-based survey sampling from leading researchers
• Ideal overview for graduate students in statistics, sciences, and social sciences

Readership: Graduates and researchers in statistics, science, and social sciences as well as professional statisticians.

Ray Chambers, School of Mathematics and Applied Statistics, University of Wollongong, Australia, and Robert Clark, School of Mathematics and Applied Statistics, University of Wollongong, Australia

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