{"product_id":"9781118735725","title":"Small Area Estimation","description":"\u003cp\u003e\u003cb\u003ePraise for the \u003ci\u003eFirst Edition\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e\"This pioneering work, in which Rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic.... I believe that it has the potential to turn small area estimation...into a larger area of importance to both researchers and practitioners.\";\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e\u003ci\u003e—Journal of the American Statistical Association\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWritten by two experts in the field, \u003ci\u003eSmall Area Estimation, Second Edition \u003c\/i\u003eprovides a comprehensive and up-to-date account of the methods and theory of small area estimation (SAE), particularly indirect estimation based on explicit small area linking models. The model-based approach to small area estimation offers several advantages including increased precision, the derivation of “optimal” estimates and associated measures of variability under an assumed model, and the validation of models from the sample data.\u003c\/p\u003e \u003cp\u003eEmphasizing real data throughout, the \u003ci\u003eSecond Edition \u003c\/i\u003emaintains a self-contained account of crucial theoretical and methodological developments in the field of SAE. The new edition provides extensive accounts of new and updated research, which often involves complex theory to handle model misspecifications and other complexities. In addition to the information on survey design issues and traditional methods employing indirect estimates based on implicit linking models, \u003ci\u003eSmall Area Estimation, Second Edition \u003c\/i\u003ealso features:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eAdditional sections describe an R package for SAE and applications with R data sets that readers can replicate\u003c\/li\u003e \u003cli\u003eNumerous examples of SAE applications throughout the book, including recent applications in U.S. Federal programs\u003c\/li\u003e \u003cli\u003eNew topical coverage on extended design issues, synthetic estimation, further refinements and solutions to the Fay-Herriot area level model, basic unit level models, and spatial and time series models\u003c\/li\u003e \u003cli\u003eA discussion of the advantages and limitations of various SAE methods for model selection from data as well as comparisons of estimates derived from models to reliable values obtained from external sources, such as previous census or administrative data\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eSmall Area Estimation, Second Edition \u003c\/i\u003eis an excellent reference for practicing statisticians and survey methodologists as well as practitioners interested in learning SAE methods. The \u003ci\u003eSecond Edition \u003c\/i\u003eis also an ideal textbook for graduate-level courses in SAE and reliable small area statistics.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47121650352368,"sku":"9781118735725","price":110.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781118735725_p0.jpg?v=1769889455","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781118735725","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}