Incomplete Data in Sample Surveys: Report and case studies
Author | : William Gregory Madow |
Publisher | : |
Total Pages | : |
Release | : 1900 |
Genre | : Sampling (Statistics) |
ISBN | : |
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Author | : William Gregory Madow |
Publisher | : |
Total Pages | : |
Release | : 1900 |
Genre | : Sampling (Statistics) |
ISBN | : |
Author | : |
Publisher | : |
Total Pages | : 0 |
Release | : 1983 |
Genre | : Sampling (Statistics) |
ISBN | : 9780123639011 |
Author | : William Gregory Madow |
Publisher | : |
Total Pages | : 528 |
Release | : 1983 |
Genre | : Mathematics |
ISBN | : |
Author | : William Gregory Madow |
Publisher | : |
Total Pages | : 454 |
Release | : 1983 |
Genre | : Sampling (Statistics). |
ISBN | : |
Author | : William Gregory Madow |
Publisher | : |
Total Pages | : 0 |
Release | : 1983 |
Genre | : Sampling (Statistics) |
ISBN | : 9780123639011 |
Author | : National Research Council (U.S.). Panel on Incomplete Data |
Publisher | : |
Total Pages | : 616 |
Release | : 1983 |
Genre | : Mathematics |
ISBN | : |
Author | : Paul J. Lavrakas |
Publisher | : SAGE Publications |
Total Pages | : 1073 |
Release | : 2008-09-12 |
Genre | : Social Science |
ISBN | : 150631788X |
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.
Author | : Roderick J. A. Little |
Publisher | : John Wiley & Sons |
Total Pages | : 465 |
Release | : 2019-03-19 |
Genre | : Mathematics |
ISBN | : 1118596013 |
An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism, and then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated “classic” written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography The authors were awarded The Karl Pearson Prize in 2017 by the International Statistical Institute, for a research contribution that has had profound influence on statistical theory, methodology or applications. Their work "has been no less than defining and transforming." (ISI) Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry.
Author | : Donald B. Rubin |
Publisher | : John Wiley & Sons |
Total Pages | : 258 |
Release | : 2009-09-25 |
Genre | : Mathematics |
ISBN | : 0470317361 |
Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations. Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique for researchers who must analyze them. Also presents the background for Bayesian and frequentist theory. After establishing that only standard complete-data methods are needed to analyze a multiply-imputed set, the text evaluates procedures in general circumstances, outlining specific procedures for creating imputations in both the ignorable and nonignorable cases. Examples and exercises reinforce ideas, and the interplay of Bayesian and frequentist ideas presents a unified picture of modern statistics.