Non-response in sample surveys can have serious consequences on the accuracy of survey results. This study shows how high response rates can be achieved, even in the Netherlands, a country notorious for its low response rates. As an introduction, an overview of groups that generally have low response rates and the possible causes of their lack of response is presented. The emphasis is on non-response bias that occurs when non-response behavior and survey outcomes are correlated, independent of background characteristics. The Hunt for the Last Respondent will be of interest to survey methodologists, market researchers, survey sponsors, and survey statisticians, as well as anyone interested in survey quality.
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.
A thorough and comprehensive guide to the theoretical, practical, and methodological approaches used in survey experiments across disciplines such as political science, health sciences, sociology, economics, psychology, and marketing This book explores and explains the broad range of experimental designs embedded in surveys that use both probability and non-probability samples. It approaches the usage of survey-based experiments with a Total Survey Error (TSE) perspective, which provides insight on the strengths and weaknesses of the techniques used. Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment addresses experiments on within-unit coverage, reducing nonresponse, question and questionnaire design, minimizing interview measurement bias, using adaptive design, trend data, vignettes, the analysis of data from survey experiments, and other topics, across social, behavioral, and marketing science domains. Each chapter begins with a description of the experimental method or application and its importance, followed by reference to relevant literature. At least one detailed original experimental case study then follows to illustrate the experimental method’s deployment, implementation, and analysis from a TSE perspective. The chapters conclude with theoretical and practical implications on the usage of the experimental method addressed. In summary, this book: Fills a gap in the current literature by successfully combining the subjects of survey methodology and experimental methodology in an effort to maximize both internal validity and external validity Offers a wide range of types of experimentation in survey research with in-depth attention to their various methodologies and applications Is edited by internationally recognized experts in the field of survey research/methodology and in the usage of survey-based experimentation —featuring contributions from across a variety of disciplines in the social and behavioral sciences Presents advances in the field of survey experiments, as well as relevant references in each chapter for further study Includes more than 20 types of original experiments carried out within probability sample surveys Addresses myriad practical and operational aspects for designing, implementing, and analyzing survey-based experiments by using a Total Survey Error perspective to address the strengths and weaknesses of each experimental technique and method Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment is an ideal reference for survey researchers and practitioners in areas such political science, health sciences, sociology, economics, psychology, public policy, data collection, data science, and marketing. It is also a very useful textbook for graduate-level courses on survey experiments and survey methodology.
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.
