Mixed-mode surveys have become a standard at many statistical institutes. However, the introduction of multiple modes in one design goes with challenges to both methodology and logistics. Mode-specific representation and measurement differences become explicit and demand for solutions in data collection design, questionnaire design, and estimation. This is especially true when surveys are repeated and are input to long time series of official statistics. So how can statistical institutes deal with such changes? What are the origins of mode-specific error? And how can they be dealt with? In this book, the authors provide answers to these questions, and much more. Features Concise introduction to all the key elements of mixed-mode survey design and analysis Realistic official statistics examples from three general population surveys Suitable for survey managers and survey statisticians alike An overview of mode-specific representation and measurement errors and how to avoid, reduce and adjust them

Mixed-mode surveys have become a standard at many statistical institutes. However, the introduction of multiple modes in one design goes with challenges to both methodology and logistics. Mode-specific representation and measurement differences become explicit and demand for solutions in data collection design, questionnaire design, and estimation. This is especially true when surveys are repeated and are input to long time series of official statistics. So how can statistical institutes deal with such changes? What are the origins of mode-specific error? And how can they be dealt with? In this book, the authors provide answers to these questions, and much more. Features Concise introduction to all the key elements of mixed-mode survey design and analysis Realistic official statistics examples from three general population surveys Suitable for survey managers and survey statisticians alike An overview of mode-specific representation and measurement errors and how to avoid, reduce and adjust them.

The classic survey design reference, updated for the digital age For over two decades, Dillman's classic text on survey design has aided both students and professionals in effectively planning and conducting mail, telephone, and, more recently, Internet surveys. The new edition is thoroughly updated and revised, and covers all aspects of survey research. It features expanded coverage of mobile phones, tablets, and the use of do-it-yourself surveys, and Dillman's unique Tailored Design Method is also thoroughly explained. This invaluable resource is crucial for any researcher seeking to increase response rates and obtain high-quality feedback from survey questions. Consistent with current emphasis on the visual and aural, the new edition is complemented by copious examples within the text and accompanying website. This heavily revised Fourth Edition includes: Strategies and tactics for determining the needs of a given survey, how to design it, and how to effectively administer it How and when to use mail, telephone, and Internet surveys to maximum advantage Proven techniques to increase response rates Guidance on how to obtain high-quality feedback from mail, electronic, and other self-administered surveys Direction on how to construct effective questionnaires, including considerations of layout The effects of sponsorship on the response rates of surveys Use of capabilities provided by newly mass-used media: interactivity, presentation of aural and visual stimuli. The Fourth Edition reintroduces the telephone—including coordinating land and mobile. Grounded in the best research, the book offers practical how-to guidelines and detailed examples for practitioners and students alike.

Develops a theoretically based system guided by principles of social exchange and administration that ensure high quality surveys at low cost. Presents step-by-step procedures and shows why each step is important. Contains many examples and, where appropriate, contrasts acceptable and unacceptable procedures.

Covers the latest methodologies and research on international comparative surveys with contributions from noted experts in the field Advances in Comparative Survey Methodology examines the most recent advances in methodology and operations as well as the technical developments in international survey research. With contributions from a panel of international experts, the text includes information on the use of Big Data in concert with survey data, collecting biomarkers, the human subject regulatory environment, innovations in data collection methodology and sampling techniques, use of paradata across the survey lifecycle, metadata standards for dissemination, and new analytical techniques. This important resource: Contains contributions from key experts in their respective fields of study from around the globe Highlights innovative approaches in resource poor settings, and innovative approaches to combining survey and other data Includes material that is organized within the total survey error framework Presents extensive and up-to-date references throughout the book Written for students and academic survey researchers and market researchers engaged in comparative projects, this text represents a unique collaboration that features the latest methodologies and research on global comparative surveys.

Highlighting the progress made by researchers in using Web-based surveys for data collection, this timely volume summarizes the experiences of leading behavioral and social scientists from Europe and the US who collected data using the Internet. Some chapters present theory, methodology, design, and implementation, while others focus on best practice examples and/or issues such as data quality and understanding paradata. A number of contributors applied innovative Web-based research methods to the LISS panel of CentERdata collected from over 5,000 Dutch households. Their findings are presented in the book. Some of the data is available on the book website. The book addresses practical issues such as data quality, how to reach difficult target groups, how to design a survey to maximize response, and ethical issues that need to be considered. Innovative applications such as the use of biomarkers and eye-tracking techniques are also explored. Part 1 provides an overview of Internet survey research including its methodologies, strengths, challenges, and best practices. Innovative ways to minimize sources of error are provided along with a review of mixed-mode designs, how to design a scientifically sound longitudinal panel and avoid sampling problems, and address ethical requirements in Web surveys. Part 2 focuses on advanced applications including the impact of visual design on the interpretability of survey questions, the impact survey usability has on respondents’ answers, design features that increase interaction, and how Internet surveys can be effectively used to study sensitive issues. Part 3 addresses data quality, sample selection, measurement and non-response error, and new applications for collecting online data. The issue of underrepresentation of certain groups in Internet research and the measures most effective at reducing it are also addressed. The book concludes with a discussion of the importance of paradata and the Web data collection process in general, followed by chapters with innovative experiments using eye-tracking techniques and biomarker data. This practical book appeals to practitioners from market survey research institutes and researchers in disciplines such as psychology, education, sociology, political science, health studies, marketing, economics, and business who use the Internet for data collection, but is also an ideal supplement for graduate and/or upper level undergraduate courses on (Internet) research methods and/or data collection taught in these fields.

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.