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Sampling Statistics
von Wayne A. FullerDiscover the latest developments and current practices in surveysampling
Survey sampling is an important component of research in manyfields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical andscientifically reliable are essential to planning statisticalresearch and the design of experiments. Sampling Statisticspresents estimation techniques and sampling concepts to facilitatethe application of model-based procedures to survey samples.
The book begins with an introduction to standard probabilitysampling concepts, which provides the foundation for studyingsamples selected from a finite population. The development of thetheory of complex sampling methods is detailed, and subsequentchapters explore the construction of estimators, sample design, replication variance estimation, and procedures such as nonresponseadjustment and small area estimation where models play a key role. A final chapter covers analytic studies in which survey data areused for the estimation of parameters for a subject mattermodel.
The author draws upon his extensive experience with surveysamples in the book's numerous examples. Both the production of„general use“ databases and the analytic study of a limited numberof characteristics are discussed. Exercises at the end of eachchapter allow readers to test their comprehension of the presentedconcepts and techniques, and the references provide furtherresources for study.
Sampling Statistics is an ideal book for courses insurvey sampling at the graduate level. It is also a valuablereference for practicing statisticians who analyze survey data orare involved in the design of sample surveys.
Survey sampling is an important component of research in manyfields, and as the importance of survey sampling continues to grow, sophisticated sampling techniques that are both economical andscientifically reliable are essential to planning statisticalresearch and the design of experiments. Sampling Statisticspresents estimation techniques and sampling concepts to facilitatethe application of model-based procedures to survey samples.
The book begins with an introduction to standard probabilitysampling concepts, which provides the foundation for studyingsamples selected from a finite population. The development of thetheory of complex sampling methods is detailed, and subsequentchapters explore the construction of estimators, sample design, replication variance estimation, and procedures such as nonresponseadjustment and small area estimation where models play a key role. A final chapter covers analytic studies in which survey data areused for the estimation of parameters for a subject mattermodel.
The author draws upon his extensive experience with surveysamples in the book's numerous examples. Both the production of„general use“ databases and the analytic study of a limited numberof characteristics are discussed. Exercises at the end of eachchapter allow readers to test their comprehension of the presentedconcepts and techniques, and the references provide furtherresources for study.
Sampling Statistics is an ideal book for courses insurvey sampling at the graduate level. It is also a valuablereference for practicing statisticians who analyze survey data orare involved in the design of sample surveys.
