The Science of Web Surveys

Hardcover | May 10, 2013

byRoger Tourangeau, Frederick Conrad, Mick P. Couper

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The development and widespread use of Web surveys have resulted in an outpouring of research on their design. In this volume, Tourangeau, Conrad, and Couper provide a comprehensive summary and synthesis of the literature on this increasingly popular method of data collection. The book includesnew integration of the authors' work with other important research on Web surveys, including a meta-analysis of studies that compare reports on sensitive topics in Web surveys with reports collected in other modes of data collection. Adopting the total survey error framework, the book examinessampling and coverage issues, nonresponse, measurement, and the issues involved in combining modes. In addition, the conclusion provides a model for understanding the errors in estimates that combine data collected in more than one mode. Web surveys have several important characteristics that affect their ability to collect accurate survey data. Discussing these in detail, the authors address basic design decisions from input widgets to background colors. They additionally focus on the visual character of Web surveys, on theirability to automatically interact with respondents, and on the Web as a method of self-administration. The Science of Web Surveys is relevant for those with the practical goal of improving their own surveys and those with an interest in understanding an increasingly important method of datacollection.

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The development and widespread use of Web surveys have resulted in an outpouring of research on their design. In this volume, Tourangeau, Conrad, and Couper provide a comprehensive summary and synthesis of the literature on this increasingly popular method of data collection. The book includesnew integration of the authors' work with o...

Roger Tourangeau is a Vice President and Associate Director at Westat, one of the largest survey firms in the U.S. Before joining Westat, he was Research Professor at the University of Michigan's Survey Research Center and the Director of the Joint Program in Survey Methodology at the University of Maryland. He has been a survey method...

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Format:HardcoverDimensions:224 pages, 10 × 7 × 0.98 inPublished:May 10, 2013Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0199747040

ISBN - 13:9780199747047

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Table of Contents

Preface1. Introduction1.1 The Total Survey Error Approach1.2 Roadmap of the Book1.3 The Purpose and Scope of the Book2. Sampling and Coverage Issues for Web Surveys2.1 Types of Web Surveys and the Use of Probability Sampling2.2 Coverage Issues for Web Surveys2.3 Statistical Corrections for Coverage and Sampling Bias2.4 Summary3. Nonresponse in Web Surveys3.1 Defining Nonresponse and Nonresponse Error in Web Surveys3.2 Nonresponse Error in Web Surveys3.3 Response and Participation Rates in Web Surveys3.4 Factors Affecting Participation in Web Surveys3.5 Nonresponse in Mixed-Mode Surveys3.6 Factors Affecting Breakoffs in Web Surveys3.7 Item Nonresponse in Web Surveys3.8 Summary4. Introduction to Measurement and Design in Web Surveys4.1 Measurement Error in Web Surveys4.2 Measurement Features of Web Surveys4.3 Choice of Broad Design Approaches4.4 The Look and Feel of the Web Survey4.5 Navigation Conventions4.6 Choice of Response Formats4.7 Grid of Matrix Questions4.8 Summary5. The Web as a Visual Medium5.1 Interpreting Visual Features of Web Questionnaires5.2 The Impact of Images5.3 The Concept of Visibility5.4 Summary6. Interactive Features and Measurement Error6.1 Dimensions of Interactivity6.2 Responsive, Machine-Like Features6.2.1 Progress Indicators6.2.2 Running Tallies6.2.3 Visual Analog Scales6.2.4 Interactive Grids6.2.5 Online Definitions6.3 Human-Like Interactive Features6.4 Summary7. Measurement Error on the Web and in Other Modes of Data Collection7.1 Conceptual Schemes for Understanding Mode Effects7.2 Web Surveys as a Method of Self-Administration7.3 Web Surveys and Cognitive Burden7.4 Summary8. Summary and Conclusions8.1 Non-Observation Errors in Web Surveys8.2 Observation Errors8.3 A Model for Mode Effects8.4 Recommendations for Web Surveys8.5 The Future of Web SurveysReferencesAuthor IndexSubject Index