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Sample surveys : inference and analysis /
This new handbook contains the most comprehensive account of sample surveys theory and practice to date. It is a second volume on sample surveys, with the goal of updating and extending the sampling volume published as volume 6 of the Handbook of Statistics in 1988. The present handbook is divided i...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Boston :
Elsevier/North-Holland,
2009.
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| Colección: | Handbook of statistics (Amsterdam, Netherlands) ;
v. 29B. |
| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
Tabla de Contenidos:
- Front Cover; Title Page; Copyright Page; Preface to Handbook 29B; Table of Contents; Contributors: Vol. 29B; Part 4: Alternative Approaches to Inference from Survey Data; Introduction to Part 4; 1. Introduction; 2. Modes of inference with survey data; 3. Overview of Part 4; Chapter 23. Model-Based Prediction of Finite Population Totals; 1. Superpopulation models and some simple examples; 2. Prediction under the general linear model; 3. Estimation weights; 4. Weighted balance and robustness; 5. Variance estimation; 6. Models with qualitative auxiliaries; 7. Clustered populations.
- 8. Estimation under nonlinear modelsChapter 24. Design- and Model-Based Inference for Model Parameters; 1. Introduction and scope; 2. Survey populations and target populations; 3. Statistical inferences; 4. General theory for fitting models; 5. Cases where design-based methods can be problematic; 6. Estimation of design-based variances; 7. Integrating data from more than one survey; 8. Some final remarks; Chapter 25. Calibration Weighting: Combining Probability Samples and Linear Prediction Models; 1. Introduction; 2. Randomization consistency and other asymptotic properties.
- 3. The GREG estimator4. Redefining calibration weights; 5. Variance estimation; 6. Nonlinear calibration; 7. Calibration and quasi-randomization; 8. Other approaches, other issues; Acknowledgements; Chapter 26. Estimating Functions and Survey Sampling; 1. Introduction; 2. Defining finite population and superpopulation parameters through estimating functions; 3. Design-unbiased estimating functions; 4. Optimality; 5. Asymptotic properties of sample estimating functions and their roots; 6. Interval estimation from estimating functions; 7. Bootstrapping estimating functions.
- 8. Multivariate and nuisance parameters9. Estimating functions and imputation; Acknowledgment; Chapter 27. Nonparametric and Semiparametric Estimation in Complex Surveys; 1. Introduction; 2. Nonparametric methods in descriptive inference from surveys; 3. Nonparametric methods in analytic inference from surveys; 4. Nonparametric methods in nonresponse adjustment; 5. Nonparametric methods in small area estimation; Chapter 28. Resampling Methods in Surveys; 1. Introduction; 2. The basic notions of bootstrap and jackknife; 3. Methods for more complex survey designs and estimators.
- 4. Variance estimation in the presence of imputation5. Resampling methods for sampling designs in two phases; 6. Resampling methods in the prediction approach; 7. Resampling methods in small area estimation; 8. Discussion; Acknowledgments; Chapter 29. Bayesian Developments in Survey Sampling; 1. Introduction; 2. Notation and preliminaries; 3. The Bayesian paradigm; 4. Linear Bayes estimator; 5. Bayes estimators of the finite population mean under more complex models; 6. Stratified sampling and domain estimation; 7. Generalized linear models; 8. Summary; Acknowledgments.