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Modern statistics consists of methods which help in drawing inferences about the population under consideration. These populations may actually exist, or could be generated by repeated· experimentation. The medium of drawing inferences about the population is the sample, which is a subset of measurements selected from the population. Each measurement in the sample is used for making inferences about the population. The populations and also the methods of sample selection differ from one field of science to the other. Social scientists use surveys tocollectthe sample information, whereas the physical scientists employ the method of experimentation for obtaining this information. This is because in social sciences the factors that cause variation in the measurements on the study variable for the population units can not be controlled, whereas in physical sciences these factors can be controlled, at least to some extent, through proper experimental design. Several excellent books on sampling theory are available in the market. These books discuss the theory of sample surveys in great depth and detail, and are suited to the postgraduate students majoring in statistics. Research workers in the field of sampling methodology can also make use of these books. However, not many suitable books are available, which can be used by the students and researchers in the fields of economics, social sciences, extension education, agriculture, medical sciences, business management, etc. These students and workers usually conduct sample surveys during their research projects.
Written by one of the main figures in twentieth century statistics, this book provides a unified treatment of first-order large-sample theory. It discusses a broad range of applications including introductions to density estimation, the bootstrap, and the asymptotics of survey methodology. The book is written at an elementary level making it accessible to most readers.
The three parts of this book on survey methodology combine an introduction to basic sampling theory, engaging presentation of topics that reflect current research trends, and informed discussion of the problems commonly encountered in survey practice. These related aspects of survey methodology rarely appear together under a single connected roof, making this book a unique combination of materials for teaching, research and practice in survey sampling. Basic knowledge of probability theory and statistical inference is assumed, but no prior exposure to survey sampling is required. The first part focuses on the design-based approach to finite population sampling. It contains a rigorous coverage of basic sampling designs, related estimation theory, model-based prediction approach, and model-assisted estimation methods. The second part stems from original research conducted by the authors as well as important methodological advances in the field during the past three decades. Topics include calibration weighting methods, regression analysis and survey weighted estimating equation (EE) theory, longitudinal surveys and generalized estimating equations (GEE) analysis, variance estimation and resampling techniques, empirical likelihood methods for complex surveys, handling missing data and non-response, and Bayesian inference for survey data. The third part provides guidance and tools on practical aspects of large-scale surveys, such as training and quality control, frame construction, choices of survey designs, strategies for reducing non-response, and weight calculation. These procedures are illustrated through real-world surveys. Several specialized topics are also discussed in detail, including household surveys, telephone and web surveys, natural resource inventory surveys, adaptive and network surveys, dual-frame and multiple frame surveys, and analysis of non-probability survey samples. This book is a self-contained introduction to survey sampling that provides a strong theoretical base with coverage of current research trends and pragmatic guidance and tools for conducting surveys.
This edition is a reprint of the second edition published by Cengage Learning, Inc. Reprinted with permission. What is the unemployment rate? How many adults have high blood pressure? What is the total area of land planted with soybeans? Sampling: Design and Analysis tells you how to design and analyze surveys to answer these and other questions. This authoritative text, used as a standard reference by numerous survey organizations, teaches sampling using real data sets from social sciences, public opinion research, medicine, public health, economics, agriculture, ecology, and other fields. The book is accessible to students from a wide range of statistical backgrounds. By appropriate choice of sections, it can be used for a graduate class for statistics students or for a class with students from business, sociology, psychology, or biology. Readers should be familiar with concepts from an introductory statistics class including linear regression; optional sections contain the statistical theory, for readers who have studied mathematical statistics. Distinctive features include: More than 450 exercises. In each chapter, Introductory Exercises develop skills, Working with Data Exercises give practice with data from surveys, Working with Theory Exercises allow students to investigate statistical properties of estimators, and Projects and Activities Exercises integrate concepts. A solutions manual is available. An emphasis on survey design. Coverage of simple random, stratified, and cluster sampling; ratio estimation; constructing survey weights; jackknife and bootstrap; nonresponse; chi-squared tests and regression analysis. Graphing data from surveys. Computer code using SAS® software. Online supplements containing data sets, computer programs, and additional material. Sharon Lohr, the author of Measuring Crime: Behind the Statistics, has published widely about survey sampling and statistical methods for education, public policy, law, and crime. She has been recognized as Fellow of the American Statistical Association, elected member of the International Statistical Institute, and recipient of the Gertrude M. Cox Statistics Award and the Deming Lecturer Award. Formerly Dean’s Distinguished Professor of Statistics at Arizona State University and a Vice President at Westat, she is now a freelance statistical consultant and writer. Visit her website at www.sharonlohr.com.
Written for students taking research methods courses, this text provides a thorough overview of sampling principles. The author gives detailed, nontechnical descriptions and guidelines with limited presentation of formulas to help students reach basic research decisions, such as whether to choose a census or a sample, as well as how to select sample size and sample type. Intended for students and researchers in the social and behavioral sciences, public health research, marketing research, and related areas, the text provides nonstatisticians with the concepts and techniques they need to do quality work and make good sampling choices.
To the uninformed, surveys appear to be an easy type of research to design and conduct, but when students and professionals delve deeper, they encounter the vast complexities that the range and practice of survey methods present. To complicate matters, technology has rapidly affected the way surveys can be conducted; today, surveys are conducted via cell phone, the Internet, email, interactive voice response, and other technology-based modes. Thus, students, researchers, and professionals need both a comprehensive understanding of these complexities and a revised set of tools to meet the challenges. In conjunction with top survey researchers around the world and with Nielsen Media Research serving as the corporate sponsor, the Encyclopedia of Survey Research Methods presents state-of-the-art information and methodological examples from the field of survey research. Although there are other "how-to" guides and references texts on survey research, none is as comprehensive as this Encyclopedia, and none presents the material in such a focused and approachable manner. With more than 600 entries, this resource uses a Total Survey Error perspective that considers all aspects of possible survey error from a cost-benefit standpoint. Key Features Covers all major facets of survey research methodology, from selecting the sample design and the sampling frame, designing and pretesting the questionnaire, data collection, and data coding, to the thorny issues surrounding diminishing response rates, confidentiality, privacy, informed consent and other ethical issues, data weighting, and data analyses Presents a Reader′s Guide to organize entries around themes or specific topics and easily guide users to areas of interest Offers cross-referenced terms, a brief listing of Further Readings, and stable Web site URLs following most entries The Encyclopedia of Survey Research Methods is specifically written to appeal to beginning, intermediate, and advanced students, practitioners, researchers, consultants, and consumers of survey-based information.
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
Research Methods in Education introduces research methods as an integrated set of techniques for investigating questions about the educational world. This lively, innovative text helps students connect technique and substance, appreciate the value of both qualitative and quantitative methodologies, and make ethical research decisions. It weaves actual research "stories" into the presentation of research topics, and it emphasizes validity, authenticity, and practical significance as overarching research goals. The text is divided into three sections: Foundations of Research (5 chapters), Research Design and Data Collection (7 chapters), and Analyzing and Reporting Data (3 chapters). This tripartite conceptual framework honors traditional quantitative approaches while reflecting the growing popularity of qualitative studies, mixed method designs, and school-based techniques. This approach provides a comprehensive, conceptually unified, and well-written introduction to the exciting but complex field of educational research.
Now available in paperback, this book provides a comprehensive account of survey sampling theory and methodology suitable for students and researchers across a variety of disciplines. It shows how statistical modeling is a vital component of the sampling process and in the choice of estimation technique. The first textbook that systematically extends traditional sampling theory with the aid of a modern model assisted outlook. Covers classical topics as well as areas where significant new developments have taken place.
Sampling is fundamental to nearly every study in the social and policy sciences, yet clear, concise guidance for practitioners and graduate students has been difficult to find. Practical Sampling provides guidance for researchers dealing with the everyday problems of sampling. Using the practical design approach Henry integrates sampling into the overall research design and explains the interrelationships between research design and sampling choices. He lays out alternatives and implications of the choices using four detailed examples to illustrate the alternatives selected and the trade-offs made by applied researchers. The author uses a narrative, conceptual approach throughout the book; mathematical presentations are limited to necessary formulas; and calculations are kept to the absolute minimum, making it an easily approachable book for any researcher, student or professional across the social sciences.