The increasing diversity of population of the United States presents many challenges to conducting health research that is representative and informative. Dispersion and accessibility issues can increase logistical costs; populations for which it is difficult to obtain adequate sample size are also likely to be expensive to study. Hence, even if it is technically feasible to study a small population, it may not be easy to obtain the funding to do so. In order to address the issues associated with improving health research of small populations, the National Academies of Sciences, Engineering, and Medicine convened a workshop in January 2018. Participants considered ways of addressing the challenges of conducting epidemiological studies or intervention research with small population groups, including alternative study designs, innovative methodologies for data collection, and innovative statistical techniques for analysis.

Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling. The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students. - Covers a wide spectrum of topics on survey sampling and statistics - Serves as an ideal text for graduate students and researchers in survey sampling theory and applications - Contains material on recent developments in survey sampling not covered in other books - Illustrates theories using numerical examples and exercises

This is a comprehensive exposition of survey sampling useful both to the students of statistics for the course on sample survey and to the survey statisticians and practitioners involved in consultancy services, marketing, opinion polls, and so on. The text offers updated review of difficult classical techniques of survey sampling, besides covering prediction-theoretic approach of survey sampling and nonsampling errors. NEW TO THIS EDITION Two new chapters—Nonparametric Methods of Variance Estimation (Chapter 19) and Analysis of Complex Surveys (Chapter 20)—have been added. These would greatly benefit the readers. KEY FEATURES  Covers concepts of unequal probability sampling.  Provides problems of making inference from finite population using tools of classical inference.  Describes nonsampling errors including Randomised Response Techniques.  Gives over 70 worked-out examples and more than 120 problems and solutions.  Supplies live data from India and Sweden—in examples and exercises. What the Reviewer says: This is a very comprehensive modern text on survey sampling with a strong slant towards theoretical results. The book is an excellent reference book and would be a good graduate level sampling text for a course with an emphasis on sampling theory. — JESSE C. ARNOLD, Virginia Polytechnic Institute and State University