In 1991, a subcommittee of the Federal Committee on Statistical Methodology met to document the use of indirect estimators - that is, estimators which use data drawn from a domain or time different from the domain or time for which an estimate is required. This volume comprises the eight reports which describe the use of indirect estimators and they are based on case studies from a variety of federal programs. As a result, many researchers will find this book provides a valuable survey of how indirect estimators are used in practice and which addresses some of the pitfalls of these methods.

Praise for the First Edition "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." —Journal of the American Statistical Association Written by two experts in the field, Small Area Estimation, Second Edition provides 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. Emphasizing real data throughout, the Second Edition maintains 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. Including information on survey design issues and traditional methods employing indirect estimates based on implicit linking models, Small Area Estimation, Second Edition also features: Additional sections describing the use of R code data sets for readers to use when replicating applications Numerous examples of SAE applications throughout each chapter, including recent applications in U.S. Federal programs New 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 A 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 Small Area Estimation, Second Edition is an excellent reference for practicing statisticians and survey methodologists as well as practitioners interested in learning SAE methods. The Second Edition is also an ideal textbook for graduate-level courses in SAE and reliable small area statistics.

Federal household surveys today face several significant challenges including: increasing costs of data collection, declining response rates, perceptions of increasing response burden, inadequate timeliness of estimates, discrepant estimates of key indicators, inefficient and considerable duplication of some survey content, and instances of gaps in needed research and analysis. The Workshop on the Future of Federal Household Surveys, held at the request of the U.S. Census Bureau, was designed to address the increasing concern among many members of the federal statistical system that federal household data collections in their current form are unsustainable. The workshop brought together leaders in the statistical community to discuss opportunities for enhancing the relevance, quality, and cost-effectiveness of household surveys sponsored by the federal statistical system. The Future of Federal Household Surveys is a factual summary of the presentations and related discussions that transpired during the workshop. This summary includes a number of solutions that range from methodological approaches, such as the use of administrative data, to emphasis on interagency cooperative efforts.

This is one of two volumes that sets forth invited papers presented at the International Indian Statistical Association Conference. This volume emphasizes advancements in methodology and applications of probability and statistics. The chapters, representing the ideas of vanguard researchers on the topic, present several different subspecialties, including applied probability, models and applications, estimation and testing, robust inference, regression and design and sample size methodology. The text also fully describes the applications of these new ideas to industry, ecology, biology, health, economics and management. Researchers and graduate students in mathematical analysis, as well as probability and statistics professionals in industry, will learn much from this volume.