Finite Population Sampling and Inference: A Prediction Approach / Edition 1 available in Hardcover
- Pub. Date:
Complete coverage of the prediction approach to survey sampling ina single resourcePrediction theory has been extremely influential in survey samplingfor nearly three decades, yet research findings on this model-basedapproach are scattered in disparate areas of the statisticalliterature. Finite Population Sampling and Inference: A PredictionApproach presents for the first time a unified treatment of sampledesign and estimation for finite populations from a predictionpoint of view, providing readers with access to a wealth oftheoretical results, including many new results and, a variety ofpractical applications. Geared to theoretical statisticians andpractitioners alike, the book discusses all topics from the groundup and clearly explains the relation of the prediction approach tothe traditional design-based randomization approach. Key featuresinclude:* Special emphasis on linking survey sampling to mainstreamstatistics through extensive use of general linear models* A liberal use of simulation studies, numerical examples, andexercises illustrating theoretical results* Numerous statistical graphics showing simulation results andproperties of estimates* A library of S-Plus computer functions plus six real populations,available via ftp* Over 260 references to finite population sampling, linear models,and other relevant literature
About the Author
RICHARD VALLIANT, PhD, is Associate Director at Westat, Rockville,Maryland.ALAN H. DORFMAN, PhD, is Senior Mathematical Statistician for theBureau of Labor Statistics, Washington, D.C.RICHARD M. ROYALL, PhD, is Professor of Biostatistics, JohnsHopkins University, Baltimore, Maryland.
Table of ContentsIntroduction to Prediction Theory.Prediction Theory Under the General Linear Model.Bias-Robustness.Robustness and Efficiency.Variance Estimation.Stratified Populations.Models with Qualitative Auxiliaries.Clustered Populations.Robust Variance Estimation in Two-Stage Cluster Sampling.Alternative Variance Estimation Methods.Special Topics and Open Questions.Appendices.Bibliography.Answers to Select Exercises.Indexes.