Sampling statistics
Discover the latest developments and current practices in survey sampling Survey sampling is an important component of research in many fields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical and scientifically reliable are essen...
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| Main Author | |
|---|---|
| Format | eBook Book |
| Language | English |
| Published |
Hoboken, N.J
Wiley
2009
WILEY John Wiley & Sons, Incorporated Wiley-Blackwell |
| Edition | 1 |
| Series | Wiley Series in Survey Methodology |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9780470454602 0470454601 0470523549 9780470523544 |
| DOI | 10.1002/9780470523551 |
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| Abstract | Discover the latest developments and current practices in survey sampling Survey sampling is an important component of research in many fields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical and scientifically reliable are essential to planning statistical research and the design of experiments. Sampling Statistics presents estimation techniques and sampling concepts to facilitate the application of model-based procedures to survey samples. The book begins with an introduction to standard probability sampling concepts, which provides the foundation for studying samples selected from a finite population. The development of the theory of complex sampling methods is detailed, and subsequent chapters explore the construction of estimators, sample design, replication variance estimation, and procedures such as nonresponse adjustment and small area estimation where models play a key role. A final chapter covers analytic studies in which survey data are used for the estimation of parameters for a subject matter model. The author draws upon his extensive experience with survey samples in the book's numerous examples. Both the production of "general use" databases and the analytic study of a limited number of characteristics are discussed. Exercises at the end of each chapter allow readers to test their comprehension of the presented concepts and techniques, and the references provide further resources for study. Sampling Statistics is an ideal book for courses in survey sampling at the graduate level. It is also a valuable reference for practicing statisticians who analyze survey data or are involved in the design of sample surveys. |
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| AbstractList | Discover the latest developments and current practices in survey sampling Survey sampling is an important component of research in many fields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical and scientifically reliable are essential to planning statistical research and the design of experiments. Sampling Statistics presents estimation techniques and sampling concepts to facilitate the application of model-based procedures to survey samples. The book begins with an introduction to standard probability sampling concepts, which provides the foundation for studying samples selected from a finite population. The development of the theory of complex sampling methods is detailed, and subsequent chapters explore the construction of estimators, sample design, replication variance estimation, and procedures such as nonresponse adjustment and small area estimation where models play a key role. A final chapter covers analytic studies in which survey data are used for the estimation of parameters for a subject matter model. The author draws upon his extensive experience with survey samples in the book's numerous examples. Both the production of "general use" databases and the analytic study of a limited number of characteristics are discussed. Exercises at the end of each chapter allow readers to test their comprehension of the presented concepts and techniques, and the references provide further resources for study. Sampling Statistics is an ideal book for courses in survey sampling at the graduate level. It is also a valuable reference for practicing statisticians who analyze survey data or are involved in the design of sample surveys. |
| Author | Fuller, Wayne A |
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| DOI | 10.1002/9780470523551 |
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| Notes | Includes bibliographical references and index |
| OCLC | 299695775 466446989 |
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| PublicationPlace | Hoboken, N.J |
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| PublicationSeriesTitle | Wiley Series in Survey Methodology |
| PublicationYear | 2009 2011 |
| Publisher | Wiley WILEY John Wiley & Sons, Incorporated Wiley-Blackwell |
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| Snippet | Discover the latest developments and current practices in survey sampling Survey sampling is an important component of research in many fields, and as the... |
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| SubjectTerms | Estimation theory Mathematical statistics Mathematics Probability & Statistics Sampling (Statistics) |
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| TableOfContents | Sampling statistics -- CONTENTS -- PREFACE -- LIST OF TABLES -- LIST OF PRINCIPAL RESULTS -- LIST OF EXAMPLES -- CHAPTER 1: PROBABILITY SAMPLING FROM A FINITE UNIVERSE -- CHAPTER 2: USE OF AUXILIARY INFORMATION IN ESTIMATION -- CHAPTER 3: USE OF AUXILIARY INFORMATION IN DESIGN -- CHAPTER 4: REPLICATION VARIANCE ESTIMATION -- CHAPTER 5: MODELS USED IN CONJUNCTION WITH SAMPLING -- CHAPTER 6: ANALYTIC STUDIES -- REFERENCES -- INDEX 3.3.3 Separate samples with common characteristics -- 3.3.4 Composite estimation -- 3.4 Rejective sampling -- 3.5 References -- 3.6 Exercises -- 4 REPLICATION VARIANCE ESTIMATION -- 4.1 Introduction -- 4.2 Jackknife Variance Estimation -- 4.2.1 Introduction -- 4.2.2 Stratified samples -- 4.2.3 Quantiles -- 4.3 Balanced Half-Samples -- 4.4 Two-Phase Samples -- 4.5 The Bootstrap -- 4.6 References -- 4.7 Exercises -- 5 MODELS USED IN CONJUNCTION WITH SAMPLING -- 5.1 Nonresponse -- 5.1.1 Introduction -- 5.1.2 Response models and weighting -- 5.2 Imputation -- 5.2.1 Introduction -- 5.2.2 Fractional imputation -- 5.2.3 Nearest-neighbor imputation -- 5.2.4 Imputed estimators for domains -- 5.3 Variance Estimation -- 5.4 Outliers and Skewed Populations -- 5.5 Small Area Estimation -- 5.6 Measurement Error -- 5.6.1 Introduction -- 5.6.2 Simple estimators -- 5.6.3 Complex estimators -- 5.7 References -- 5.8 Exercises -- 6 ANALYTIC STUDIES -- 6.1 Introduction -- 6.2 Models and Simple Estimators -- 6.3 Estimation of Regression Coefficients -- 6.3.1 Ordinary least squares and tests for bias -- 6.3.2 Consistent estimators -- 6.4 Instrumental variables -- 6.4.1 Introduction -- 6.4.2 Weighted instrumental variable estimator -- 6.4.3 Instrumental variables for weighted samples -- 6.4.4 Instrumental variable pretest estimators -- 6.5 Nonlinear models -- 6.6 Cluster and multistage samples -- 6.7 Pretest procedures -- 6.8 References -- 6.9 Exercises -- REFERENCES -- Index Intro -- SAMPLING STATISTICS -- CONTENTS -- Preface -- List Of Tables -- List Of Principal Results -- List Of Examples -- 1 PROBABILITY SAMPLING FROM A FINITE UNIVERSE -- 1.1 Introduction -- 1.2 Probability Sampling -- 1.2.1 Basic properties of probability samples -- 1.2.2 Poisson sampling -- 1.2.3 Stratified sampling -- 1.2.4 Systematic sampling -- 1.2.5 Replacement sampling -- 1.2.6 Rejective sampling -- 1.2.7 Cluster samples -- 1.2.8 Two-stage sampling -- 1.3 Limit Properties -- 1.3.1 Sequences of estimators -- 1.3.2 Central limit theorems -- 1.3.3 Functions of means -- 1.3.4 Approximations for complex estimators -- 1.3.5 Quantiles -- 1.4 Methods of Unequal Probability Sample Selection -- 1.5 References -- 1.6 Exercises -- 1.7 Appendix 1 A: Some Order Concepts -- 2 USE OF AUXILIARY INFORMATION IN ESTIMATION -- 2.1 Ratio Estimation -- 2.2 Regression Estimation -- 2.2.1 Simple random sampling under the normal model -- 2.2.2 General populations and complex samples -- 2.2.3 Poststratification -- 2.2.4 Residuals for variance estimation -- 2.3 Models and Regression Estimation -- 2.3.1 Linear models -- 2.3.2 Nonlinear models -- 2.4 Regression and Stratification -- 2.5 Estimation with Conditional Probabilities -- 2.6 Regression for Two-Stage Samples -- 2.7 Calibration -- 2.8 Weight Bounds -- 2.9 Maximum Likelihood and Raking Ratio -- 2.10 References -- 2.11 Exercises -- 2.12 Appendix 2A: Missouri Data -- 3 USE OF AUXILIARY INFORMATION IN DESIGN -- 3.1 Introduction -- 3.1.1 Selection probabilities -- 3.1.2 Strata formation -- 3.1.3 Stratification and variance estimation -- 3.1.4 Controlled two-per-stratum design -- 3.1.5 Design for subpopulations -- 3.2 Multiple-Stage Samples -- 3.2.1 Cluster sampling -- 3.2.2 Two-stage sampling -- 3.3 Multiple-Phase Samples -- 3.3.1 Two-phase samples -- 3.3.2 Three-phase samples |
| Title | Sampling statistics |
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