Description
Book SynopsisAs a comprehensive textbook in survey sampling, this book discusses the inadequacies of classic, designed-based inferential procedures and provides alternative approaches in the form of model formulations, model-design-based procedures of analysis, inference and interpretation. The book focuses on a wide range of topics which included Bayesian and Empirical Bayesian approaches, complex procedures of stratification, clustering, sampling in multi stages and phases, linear and non-linear estimation of parameters, small area estimation by spatial and chronological modelling, network and adaptive sampling methods and more. The book includes detailed case studies and exercises, making it valuable for students of statistics, specifically survey sampling.
Table of Contents1. Meaning and purpose of Survey Sampling.- 2. Inference in Survey Sampling.- 3. Sampling with Varying Probabilities.- 4. Fixing the size of an Equal Probability Sample.- 5. Adjusting Unit-Nonresponse by weighting & Tackling Item-Nonresponse by Imputation.- 6. Randomized Response & Indirect Survey Techniques.- 7. Super-Population Modeling. Model-Assisted Approach.Asymptotics.- 8. Prediction Approach: Robustness, Bayesian Methods, Empirical Bayes.- 9. Small Area Estimation & Developing Small Domain Statistics.- 10. Estimation of non-linear Parametric functions.- 11. Permanent random numbers, Poisson Sampling and Collocated Sampling.- 12. Network and Adaptive Sampling.- 13. Fixing size of a sample in Complex Strategies.- 14. Inadequate and Multiple Frame Data and Conditional Inference.- 15. Study of Analytical Surveys.- An Epilogue.- References.
