Target Estimation And Adjustment Weighting For Survey Nonresponse And Sampling Bias
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| Author | : Devin Caughey |
| Publisher | : Cambridge University Press |
| Total Pages | : 98 |
| Release | : 2020-10-22 |
| Genre | : Political Science |
| ISBN | : 1108889700 |
We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully tested. After describing this workflow in abstract terms, we then describe in detail how it can be applied to the analysis of historical and contemporary opinion polls. We also discuss extensions of the basic workflow, particularly inference for causal quantities and multilevel regression and poststratification.
| Author | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 167 |
| Release | : 2013-10-26 |
| Genre | : Social Science |
| ISBN | : 0309272475 |
For many household surveys in the United States, responses rates have been steadily declining for at least the past two decades. A similar decline in survey response can be observed in all wealthy countries. Efforts to raise response rates have used such strategies as monetary incentives or repeated attempts to contact sample members and obtain completed interviews, but these strategies increase the costs of surveys. This review addresses the core issues regarding survey nonresponse. It considers why response rates are declining and what that means for the accuracy of survey results. These trends are of particular concern for the social science community, which is heavily invested in obtaining information from household surveys. The evidence to date makes it apparent that current trends in nonresponse, if not arrested, threaten to undermine the potential of household surveys to elicit information that assists in understanding social and economic issues. The trends also threaten to weaken the validity of inferences drawn from estimates based on those surveys. High nonresponse rates create the potential or risk for bias in estimates and affect survey design, data collection, estimation, and analysis. The survey community is painfully aware of these trends and has responded aggressively to these threats. The interview modes employed by surveys in the public and private sectors have proliferated as new technologies and methods have emerged and matured. To the traditional trio of mail, telephone, and face-to-face surveys have been added interactive voice response (IVR), audio computer-assisted self-interviewing (ACASI), web surveys, and a number of hybrid methods. Similarly, a growing research agenda has emerged in the past decade or so focused on seeking solutions to various aspects of the problem of survey nonresponse; the potential solutions that have been considered range from better training and deployment of interviewers to more use of incentives, better use of the information collected in the data collection, and increased use of auxiliary information from other sources in survey design and data collection. Nonresponse in Social Science Surveys: A Research Agenda also documents the increased use of information collected in the survey process in nonresponse adjustment.
| 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 | : Robert M. Groves |
| Publisher | : Wiley-Interscience |
| Total Pages | : 528 |
| Release | : 2002 |
| Genre | : Business & Economics |
| ISBN | : |
This volume offers coverage of research in the field of survey nonresponse, the primary threat to the statistical integrity of surveys. This book was written in conjunction with the International Conference on Survey Nonresponse, October 1999.
| Author | : Diana C. Mutz |
| Publisher | : Princeton University Press |
| Total Pages | : 194 |
| Release | : 2011-07-05 |
| Genre | : Social Science |
| ISBN | : 1400840481 |
Population-based survey experiments have become an invaluable tool for social scientists struggling to generalize laboratory-based results, and for survey researchers besieged by uncertainties about causality. Thanks to technological advances in recent years, experiments can now be administered to random samples of the population to which a theory applies. Yet until now, there was no self-contained resource for social scientists seeking a concise and accessible overview of this methodology, its strengths and weaknesses, and the unique challenges it poses for implementation and analysis. Drawing on examples from across the social sciences, this book covers everything you need to know to plan, implement, and analyze the results of population-based survey experiments. But it is more than just a "how to" manual. This lively book challenges conventional wisdom about internal and external validity, showing why strong causal claims need not come at the expense of external validity, and how it is now possible to execute experiments remotely using large-scale population samples. Designed for social scientists across the disciplines, Population-Based Survey Experiments provides the first complete introduction to this methodology. Offers the most comprehensive treatment of the subjectFeatures a wealth of examples and practical adviceReexamines issues of internal and external validityCan be used in conjunction with downloadable data from ExperimentCentral.org for design and analysis exercises in the classroom
| Author | : Richard Valliant |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 678 |
| Release | : 2013-05-16 |
| Genre | : Social Science |
| ISBN | : 1461464498 |
Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.
| Author | : Richard Valliant |
| Publisher | : |
| Total Pages | : 183 |
| Release | : 2018 |
| Genre | : Population |
| ISBN | : 9781597182607 |
Survey Weights: A Step-by-Step Guide to Calculation is the first guide geared toward Stata users that systematically covers the major steps taken in creating survey weights. These weights are used to project a sample to some larger population and can be computed for either probability or nonprobability samples. Sample designs can range from simple, single-stage samples to more complex, multistage samples, each of which may use specialized steps in weighting to account for selection probabilities, nonresponse, inaccurate coverage of a population by a sample, and auxiliary data to improve precision and compensate for coverage errors. The authors provide many examples with Stata code.
| Author | : Jelke Bethlehem |
| Publisher | : John Wiley & Sons |
| Total Pages | : 394 |
| Release | : 2009-05-20 |
| Genre | : Mathematics |
| ISBN | : 0470494980 |
A complete, hands-on guide to the use of statistical methods for obtaining reliable and practical survey research Applied Survey Methods provides a comprehensive outline of the complete survey process, from design to publication. Filling a gap in the current literature, this one-of-a-kind book describes both the theory and practical applications of survey research with an emphasis on the statistical aspects of survey methods. The book begins with a brief historic overview of survey research methods followed by a discussion that details the needed first steps for carrying out a survey, including the definition of a target population, the selection of a sampling frame, and the outline of a questionnaire with several examples that include common errors to avoid in the wording of questions. Throughout the book, the author provides an accessible discussion on the methodological problems that are associated with the survey process, outlining real data and examples while also providing insight on the future of survey research. Chapter coverage explores the various aspects of the survey process and the accompanying numerical techniques, including: Simple and composite sampling designs Estimators Data collection and editing The quality of results The non-response problem Weighting adjustments and methods Disclosure control The final chapter addresses the growing popularity of Web surveys, and the associated methodological problems are discussed, including solutions to common pitfalls. Exercises are provided throughout with selected answers included at the end of the book, while a related Web site features additional solutions to exercises and a downloadable demo version of the Blaise system of computer-assisted interviewing. Access to the freely available SimSam software is also available on the related Web site and provides readers with the tools needed to simulate samples from finite populations as well as visualize the effects of sample size, non-response, and the use of different estimation procedures. Applied Survey Methods is an excellent book for courses on survey research and non-response in surveys at the upper-undergraduate and graduate levels. It is also a useful reference for practicing statisticians and survey methodologists who work in both government and private research sectors.
| Author | : Taylor H. Lewis |
| Publisher | : CRC Press |
| Total Pages | : 341 |
| Release | : 2016-09-15 |
| Genre | : Mathematics |
| ISBN | : 1498776809 |
Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures. The book offers comprehensive coverage of the most essential topics, including: Drawing random samples Descriptive statistics for continuous and categorical variables Fitting and interpreting linear and logistic regression models Survival analysis Domain estimation Replication variance estimation methods Weight adjustment and imputation methods for handling missing data The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author’s website: http://mason.gmu.edu/~tlewis18/. While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation. Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.
| Author | : Changbao Wu |
| Publisher | : Springer Nature |
| Total Pages | : 371 |
| Release | : 2020-05-15 |
| Genre | : Social Science |
| ISBN | : 3030442462 |
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.
