A welcome and much-needed addition to the literature on survey data quality in social research, McNabb’s book examines the most common sources of nonsampling error: frame error; measurement error; response error, nonresponse error, and interviewer error. Offering the only comprehensive and non-technical treatment available, the book’s focus on controlling error shows readers how to eliminate the opportunity for error to occur, and features revealing examples of past and current efforts to control the incidence and effects of nonsampling error. Most importantly, it gives readers the tools they need to understand, identify, address, and prevent the most prevalent and difficult-to-control types of survey errors.
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.
Surveys enjoy great ubiquity among data collection methods in social research: they are flexible in questioning techniques, in the amount of questions asked, in the topics covered, and in the various ways of interactions with respondents. Surveys are also the preferred method by many researchers in the social sciences due to their ability to provide quick profiles and results. Because they are so commonly used and fairly easy to administer, surveys are often thought to be easily thrown together. But designing an effective survey that yields reliable and valid results takes more than merely asking questions and waiting for the answers to arrive. Geared to the non-statistician, the Handbook of Survey Methodology in Social Sciences addresses issues throughout all phases of survey design and implementation. Chapters examine the major survey methods of data collection, providing expert guidelines for asking targeted questions, improving accuracy and quality of responses, while reducing sampling and non-sampling bias. Relying on the Total Survey Error theory, various issues of both sampling and non-sampling sources of error are explored and discussed. By covering all aspects of the topic, the Handbook is suited to readers taking their first steps in survey methodology, as well as to those already involved in survey design and execution, and to those currently in training. Featured in the Handbook: • The Total Survey Error: sampling and non-sampling errors. • Survey sampling techniques. • The art of question phrasing. • Techniques for increasing response rates • A question of ethics: what is allowed in survey research? • Survey design: face-to-face, phone, mail, e-mail, online, computer-assisted.? • Dealing with sensitive issues in surveys. • Demographics of respondents: implications for future survey research. • Dealing with nonresponse, and nonresponse bias The Handbook of Survey Methodology in Social Sciences offers how-to clarity for researchers in the social and behavioral sciences and related disciplines, including sociology, criminology, criminal justice, social psychology, education, public health, political science, management, and many other disciplines relying on survey methodology as one of their main data collection tools.
Written with the needs and goals of a novice researcher in mind, this fully updated third edition provides an accurate account of how modern survey research is actually conducted. In addition to providing examples of alternative procedures, Designing Surveys shows how classic principles and recent research guide decision-making from setting the basic features of the survey through development, testing, and data collection.
In 1939, George Gallup's American Institute of Public Opinion published a pamphlet optimistically titled The New Science of Public Opinion Measurement. At the time, though, survey research was in its infancy, and only now, six decades later, can public opinion measurement be appropriately called a science, based in part on the development of the total survey error approach. Herbert F. Weisberg's handbook presents a unified method for conducting good survey research centered on the various types of errors that can occur in surveys—from measurement and nonresponse error to coverage and sampling error. Each chapter is built on theoretical elements drawn from specific disciplines, such as social psychology and statistics, and follows through with detailed treatments of the specific types of error and their potential solutions. Throughout, Weisberg is attentive to survey constraints, including time and ethical considerations, as well as controversies within the field and the effects of new technology on the survey process—from Internet surveys to those completed by phone, by mail, and in person. Practitioners and students will find this comprehensive guide particularly useful now that survey research has assumed a primary place in both public and academic circles.
The Problem with Survey Research makes a case against survey research as a primary source of reliable information. George Beam argues that all survey research instruments, all types of asking—including polls, face-to-face interviews, and focus groups—produce unreliable and potentially inaccurate results. Because those who rely on survey research only see answers to questions, it is impossible for them, or anyone else, to evaluate the results. They cannot know if the answers correspond to respondents’ actual behaviors (objective phenomena) or to their true beliefs and opinions (subjective phenomena). Reliable information can only be acquired by observation, experimentation, multiple sources of data, formal model building and testing, document analysis, and comparison. In fifteen chapters divided into six parts—Ubiquity of Survey Research, The Problem, Asking Instruments, Asking Settings, Askers, and Proper Methods and Research Designs—The Problem with Survey Research demonstrates how asking instruments, settings in which asking and answering take place, and survey researchers themselves skew results and thereby make answers unreliable. The last two chapters and appendices examine observation, other methods of data collection and research designs that may produce accurate or correct information, and shows how reliance on survey research can be overcome, and must be.
A welcome and much-needed addition to the literature on survey data quality in social research, Nonsampling Error in Social Surveys, by David E. McNabb, examines the most common sources of nonsampling error: frame error; measurement error; response error, nonresponse error, and interviewer error. Offering the only comprehensive and non-technical treatment available, the book’s focus on controlling error shows readers how to eliminate the opportunity for error to occur, and features revealing examples of past and current efforts to control the incidence and effects of nonsampling error. Most importantly, it gives readers the tools they need to understand, identify, address, and prevent the most prevalent and difficult-to-control types of survey errors.
Statistical surveys represent an important source of scientific knowledge and a valid decision support tool in many fields, from social studies to economics, market research, health studies, and others. Scientists have tackled most of the methodological issues concerning surveys and the scientific literature offers excellent proposals for planning and conducting surveys. Nevertheless, surveys often require the achievement of aims that either deviate from the methodology or do not have a specific solution at all. This book focuses on survey theory and applications, providing insight and innovative solutions to face problems in data collection and integration, complex sample design, opinion questionnaire design, and statistical estimation. Formal rigour and simple language, together with real-life examples, will make the book suitable to both practitioners involved in applied research and to academics interested in scientific developments in the survey field.
Survey Methodology is becoming a more structured field of research, deserving of more and more academic attention. The SAGE Handbook of Survey Methodology explores both the increasingly scientific endeavour of surveys and their growing complexity, as different data collection modes and information sources are combined. The handbook takes a global approach, with a team of international experts looking at local and national specificities, as well as problems of cross-national, comparative survey research. The chapters are organized into seven major sections, each of which represents a stage in the survey life-cycle: Surveys and Societies Planning a Survey Measurement Sampling Data Collection Preparing Data for Use Assessing and Improving Data Quality The SAGE Handbook of Survey Methodology is a landmark and essential tool for any scholar within the social sciences.
Featuring a timely presentation of total survey error (TSE), this edited volume introduces valuable tools for understanding and improving survey data quality in the context of evolving large-scale data sets This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields continue to evolve, leading to larger and messier data sets. This perspective challenges survey organizations to find ways to collect and process data more efficiently without sacrificing quality. The volume consists of the most up-to-date research and reporting from over 70 contributors representing the best academics and researchers from a range of fields. The chapters are broken out into five main sections: The Concept of TSE and the TSE Paradigm, Implications for Survey Design, Data Collection and Data Processing Applications, Evaluation and Improvement, and Estimation and Analysis. Each chapter introduces and examines multiple error sources, such as sampling error, measurement error, and nonresponse error, which often offer the greatest risks to data quality, while also encouraging readers not to lose sight of the less commonly studied error sources, such as coverage error, processing error, and specification error. The book also notes the relationships between errors and the ways in which efforts to reduce one type can increase another, resulting in an estimate with larger total error. This book: • Features various error sources, and the complex relationships between them, in 25 high-quality chapters on the most up-to-date research in the field of TSE • Provides comprehensive reviews of the literature on error sources as well as data collection approaches and estimation methods to reduce their effects • Presents examples of recent international events that demonstrate the effects of data error, the importance of survey data quality, and the real-world issues that arise from these errors • Spans the four pillars of the total survey error paradigm (design, data collection, evaluation and analysis) to address key data quality issues in official statistics and survey research Total Survey Error in Practice is a reference for survey researchers and data scientists in research areas that include social science, public opinion, public policy, and business. It can also be used as a textbook or supplementary material for a graduate-level course in survey research methods.
