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 "e;general use"e; 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.

Discover the latest developments and current practices in surveysamplingSurvey sampling is an important component of research in manyfields, and as the importance of survey sampling continues to growsophisticated 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 designreplication 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.

Preface ixList of Tables xiList of Principal Results xiiiList of Examples xv1 Probability Sampling from a Finite Universe 12 Use of Auxiliary Information in Estimation 953 Use of Auxiliary Information in Design 1814 Replication Variance Estimation 2515 Models Used in Conjunction with Sampling 2816 Analytic Studies 341References 391Index 449