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  • 1
    Book
    Book
    Boca Raton [u.a.] :CRC Press,
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  • 2
    Book
    Book
    Boca Raton ; London ; New York :CRC Press,
    UID:
    almahu_BV044408026
    Format: xxii, 568 Seiten : , Diagramme.
    Edition: Second edition
    ISBN: 978-1-4987-6160-4
    Series Statement: Chapmann & Hall/CRC Statistics in the Social and Behavioral Sciences Series
    Note: Literaturangaben und Index
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-1-4987-6161-1
    Language: English
    Subjects: Economics , Psychology , Sociology
    RVK:
    RVK:
    RVK:
    Keywords: Datenanalyse ; Empirische Sozialforschung ; Umfrage ; Statistik ; Sozialwissenschaften
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  • 3
    UID:
    almafu_BV022221708
    Format: XIX, 353 S. : , graph. Darst.
    ISBN: 978-1-58488-480-4 , 1-58488-480-0
    Language: English
    Subjects: Computer Science , Psychology
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    Keywords: Lineares Modell ; Gemischtes Modell ; Software
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  • 4
    UID:
    almafu_BV046870754
    Format: 1 Online-Ressource (xvii, 341 Seiten) : , Illustrationen, Diagramme.
    ISBN: 978-1-00-302021-9
    Series Statement: Statistics in the social and behavioral sciences series
    Note: Aus dem Vorwort: "On three snowy days in February 2019, scholars, students, and practitioners [...] gathered at the University of Nebraska-Lincoln (UNL) in Lincoln, Nebraska, for a workshop"
    Additional Edition: Erscheint auch als Druck-Ausgabe, Hardcover ISBN 978-0-367-89631-7
    Language: English
    Subjects: Psychology , Sociology
    RVK:
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    Keywords: Interviewer ; Interview ; Training ; Wirkung ; Methode ; Konferenzschrift ; Konferenzschrift ; Electronic books. ; Electronic books.
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (URL des Erstveröffentlichers)
    Author information: Kreuter, Frauke
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  • 5
    UID:
    almafu_9959328402502883
    Format: 1 online resource
    ISBN: 9781119041689 , 1119041686 , 9781119041702 , 1119041708
    Note: Includes index.
    Additional Edition: Print version: Total survey error in practice. Hoboken, New Jersey : John Wiley & Sons, 2016 ISBN 9781119041672
    Language: English
    Keywords: Electronic books. ; Electronic books. ; Electronic books.
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  • 6
    UID:
    gbv_1699008388
    Format: 1 Online-Ressource (346 Seiten)
    ISBN: 9781003020219 , 9781000064469 , 9781000064476 , 9781000064452
    Series Statement: ProQuest Ebook Central
    Content: Cover -- Half-Title -- Series -- Title -- Copyright -- Dedication -- Contents -- Preface -- Contributors -- About the Editors -- Section I History and Overview -- 1 The Past, Present, and Future of Research on Interviewer Effects -- 2 The Legacy of Charles Cannell -- Section II Training Interviewers -- 3 General Interviewing Techniques: Developing Evidence-based Practices for Standardized Interviewing -- 4 How to Conduct Effective Interviewer Training: A Meta-Analysis and Systematic Review -- Section III Managing and Monitoring Interviewers and the Survey Process -- 5 Exploring the Mind of the Interviewer: Findings from Research with Interviewers to Improve the Survey Process -- 6 Behavior Change Techniques for Reducing Interviewer Contributions to Total Survey Error -- 7 Statistical Identification of Fraudulent Interviews in Surveys: Improving Interviewer Controls -- 8 Examining the Utility of Interviewer Observations on the Survey Response Process -- Section IV Interviewer Effects and Interview Context and Mode -- 9 Why Do Interviewers Vary in Achieving Interview Privacy and Does Privacy Matter? -- 10 Unintended Interviewer Bias in a Community-Based Participatory Research Randomized Control Trial among American Indian Youth -- 11 Virtual Interviewers, Social Identities, and Survey Measurement Error -- 12 Differences in Interaction Quantity and Conversational Flow in CAPI and CATI Interviews -- 13 Interacting with Interviewers in Text and Voice Interviews on Smartphones -- Section V Interviewers and Nonresponse -- 14 Explaining Interviewer Effects on Survey Unit Nonresponse: A Cross-Survey Analysis -- 15 Comparing Two Methods for Managing Telephone Interview Cases -- 16 Investigating the Use of Nurse Paradata in Understanding Nonresponse to Biological Data Collection -- Section VI Interview Pace and Behaviors.
    Note: Description based on publisher supplied metadata and other sources
    Additional Edition: ISBN 9780367896317
    Additional Edition: ISBN 9780367896317
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9780367896317
    Language: English
    Keywords: Online-Publikation ; Aufsatzsammlung
    Author information: Kreuter, Frauke
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  • 7
    UID:
    kobvindex_INT58905
    Format: 1 online resource (627 pages)
    Edition: 1st ed.
    ISBN: 9781119041689
    Series Statement: Wiley Series in Survey Methodology Series
    Note: Intro -- Title Page -- Copyright Page -- Contents -- Notes on Contributors -- Preface -- Section 1 The Concept of TSE and the TSE Paradigm -- Chapter 1 The Roots and Evolution of the Total Survey Error Concept -- 1.1 Introduction and Historical Backdrop -- 1.2 Specific Error Sources and Their Control or Evaluation -- 1.3 Survey Models and Total Survey Design -- 1.4 The Advent of More Systematic Approaches Toward Survey Quality -- 1.5 What the Future Will Bring -- References -- Chapter 2 Total Twitter Error: Decomposing Public Opinion Measurement on Twitter from a Total Survey Error Perspective -- 2.1 Introduction -- 2.1.1 Social Media: A Potential Alternative to Surveys? -- 2.1.2 TSE as a Launching Point for Evaluating Social Media Error -- 2.2 Social Media: An Evolving Online Public Sphere -- 2.2.1 Nature, Norms, and Usage Behaviors of Twitter -- 2.2.2 Research on Public Opinion on Twitter -- 2.3 Components of Twitter Error -- 2.3.1 Coverage Error -- 2.3.2 Query Error -- 2.3.3 Interpretation Error -- 2.3.4 The Deviation of Unstructured Data Errors from TSE -- 2.4 Studying Public Opinion on the Twittersphere and the Potential Error Sources of Twitter Data: Two Case Studies -- 2.4.1 Research Questions and Methodology of Twitter Data Analysis -- 2.4.2 Potential Coverage Error in Twitter Examples -- 2.4.3 Potential Query Error in Twitter Examples -- 2.4.3.1 Implications of Including or Excluding RTs for Error -- 2.4.3.2 Implications of Query Iterations for Error -- 2.4.4 Potential Interpretation Error in Twitter Examples -- 2.5 Discussion -- 2.5.1 A Framework That Better Describes Twitter Data Errors -- 2.5.2 Other Subclasses of Errors to Be Investigated -- 2.6 Conclusion -- 2.6.1 What Advice We Offer for Researchers and Research Consumers -- 2.6.2 Directions for Future Research -- References -- Chapter 3 Big Data: A Survey Research Perspective , 12.5.2.1 Dashboards and Paradata , 3.1 Introduction -- 3.2 Definitions -- 3.2.1 Sources -- 3.2.2 Attributes -- 3.2.2.1 Volume -- 3.2.2.2 Variety -- 3.2.2.3 Velocity -- 3.2.2.4 Veracity -- 3.2.2.5 Variability -- 3.2.2.6 Value -- 3.2.2.7 Visualization -- 3.2.3 The Making of Big Data -- 3.3 The Analytic Challenge: From Database Marketing to Big Data and Data Science -- 3.4 Assessing Data Quality -- 3.4.1 Validity -- 3.4.2 Missingness -- 3.4.3 Representation -- 3.5 Applications in Market, Opinion, and Social Research -- 3.5.1 Adding Value through Linkage -- 3.5.2 Combining Big Data and Surveys in Market Research -- 3.6 The Ethics of Research Using Big Data -- 3.7 The Future of Surveys in a Data-Rich Environment -- References -- Chapter 4 The Role of Statistical Disclosure Limitation in Total Survey Error -- 4.1 Introduction -- 4.2 Primer on SDL -- 4.3 TSE-Aware SDL -- 4.3.1 Additive Noise -- 4.3.2 Data Swapping -- 4.4 Edit-Respecting SDL -- 4.4.1 Simulation Experiment -- 4.4.2 A Deeper Issue -- 4.5 SDL-Aware TSE -- 4.6 Full Unification of Edit, Imputation, and SDL -- 4.7 ``Big Data´´ Issues -- 4.8 Conclusion -- Acknowledgments -- References -- Section 2 Implications for Survey Design -- Chapter 5 The Undercoverage-Nonresponse Tradeoff -- 5.1 Introduction -- 5.2 Examples of the Tradeoff -- 5.3 Simple Demonstration of the Tradeoff -- 5.4 Coverage and Response Propensities and Bias -- 5.5 Simulation Study of Rates and Bias -- 5.5.1 Simulation Setup -- 5.5.2 Results for Coverage and Response Rates -- 5.5.3 Results for Undercoverage and Nonresponse Bias -- 5.5.3.1 Scenario 1 -- 5.5.3.2 Scenario 2 -- 5.5.3.3 Scenario 3 -- 5.5.3.4 Scenario 4 -- 5.5.3.5 Scenario 7 -- 5.5.4 Summary of Simulation Results -- 5.6 Costs -- 5.7 Lessons for Survey Practice -- References -- Chapter 6 Mixing Modes: Tradeoffs Among Coverage, Nonresponse, and Measurement Error Roger Tourangeau -- 6.1 Introduction , 6.2 The Effect of Offering a Choice of Modes -- 6.3 Getting People to Respond Online -- 6.4 Sequencing Different Modes of Data Collection -- 6.5 Separating the Effects of Mode on Selection and Reporting -- 6.5.1 Conceptualizing Mode Effects -- 6.5.2 Separating Observation from Nonobservation Error -- 6.5.2.1 Direct Assessment of Measurement Errors -- 6.5.2.2 Statistical Adjustments -- 6.5.2.3 Modeling Measurement Error -- 6.6 Maximizing Comparability Versus Minimizing Error -- 6.7 Conclusions -- References -- Chapter 7 Mobile Web Surveys: A Total Survey Error Perspective -- 7.1 Introduction -- 7.2 Coverage -- 7.3 Nonresponse -- 7.3.1 Unit Nonresponse -- 7.3.2 Breakoffs -- 7.3.3 Completion Times -- 7.3.4 Compliance with Special Requests -- 7.4 Measurement Error -- 7.4.1 Grouping of Questions -- 7.4.1.1 Question-Order Effects -- 7.4.1.2 Number of Items on a Page -- 7.4.1.3 Grids versus Item-By-Item -- 7.4.2 Effects of Question Type -- 7.4.2.1 Socially Undesirable Questions -- 7.4.2.2 Open-Ended Questions -- 7.4.3 Response and Scale Effects -- 7.4.3.1 Primacy Effects -- 7.4.3.2 Slider Bars and Drop-Down Questions -- 7.4.3.3 Scale Orientation -- 7.4.4 Item Missing Data -- 7.5 Links Between Different Error Sources -- 7.6 The Future of Mobile web Surveys -- References -- Chapter 8 The Effects of a Mid-Data Collection Change in Financial Incentives on Total Survey Error in the National Survey of Famil... -- 8.1 Introduction -- 8.2 Literature Review: Incentives in Face-to-Face Surveys -- 8.2.1 Nonresponse Rates -- 8.2.2 Nonresponse Bias -- 8.2.3 Measurement Error -- 8.2.4 Survey Costs -- 8.2.5 Summary -- 8.3 Data and Methods -- 8.3.1 NSFG Design: Overview -- 8.3.2 Design of Incentive Experiment -- 8.3.3 Variables -- 8.3.4 Statistical Analysis -- 8.4 Results -- 8.4.1 Nonresponse Error -- 8.4.2 Sampling Error and Costs -- 8.4.3 Measurement Error , 8.5 Conclusion -- 8.5.1 Summary -- 8.5.2 Recommendations for Practice -- References -- Chapter 9 A Total Survey Error Perspective on Surveys in Multinational, Multiregional, and Multicultural Contexts -- 9.1 Introduction -- 9.2 TSE in Multinational, Multiregional, and Multicultural Surveys -- 9.3 Challenges Related to Representation and Measurement Error Components in Comparative Surveys -- 9.3.1 Representation Error -- 9.3.1.1 Coverage Error -- 9.3.1.2 Sampling Error -- 9.3.1.3 Unit Nonresponse Error -- 9.3.1.4 Adjustment Error -- 9.3.2 Measurement Error -- 9.3.2.1 Validity -- 9.3.2.2 Measurement Error - The Response Process -- 9.3.2.3 Processing Error -- 9.4 QA and QC in 3MC Surveys -- 9.4.1 The Importance of a Solid Infrastructure -- 9.4.2 Examples of QA and QC Approaches Practiced by Some 3MC Surveys -- 9.4.3 QA/QC Recommendations -- References -- Chapter 10 Smartphone Participation in Web Surveys: Choosing Between the Potential for Coverage, Nonresponse, and Measurement Error -- 10.1 Introduction -- 10.1.1 Focus on Smartphones -- 10.1.2 Smartphone Participation: Web-Survey Design Decision Tree -- 10.1.3 Chapter Outline -- 10.2 Prevalence of Smartphone Participation in Web Surveys -- 10.3 Smartphone Participation Choices -- 10.3.1 Disallowing Smartphone Participation -- 10.3.2 Discouraging Smartphone Participation -- 10.4 Instrument Design Choices -- 10.4.1 Doing Nothing -- 10.4.2 Optimizing for Smartphones -- 10.5 Device and Design Treatment Choices -- 10.5.1 PC/Legacy versus Smartphone Designs -- 10.5.2 PC/Legacy versus PC/New -- 10.5.3 Smartphone/Legacy versus Smartphone/New -- 10.5.4 Device and Design Treatment Options -- 10.6 Conclusion -- 10.7 Future Challenges and Research Needs -- Appendix 10.A: Data Sources -- A.1 Market Strategies (17 studies) -- A.2 Experimental Data from Market Strategies International , A.3 Sustainability Cultural Indicators Program (SCIP) -- A.4 Army Study to Assess Risk and Resilience in Service members (STARRS) -- A.5 Panel Study of Income Dynamics Childhood Retrospective Circumstances Study (PSID-CRCS) -- Appendix 10.B: Smartphone Prevalence in Web Surveys -- Appendix 10.C: Screen Captures from Peterson and others (2013) Experiment -- Appendix 10.D: Survey Questions Used in the Analysis of the Peterson and others (2013) Experiment -- References -- Chapter 11 Survey Research and the Quality of Survey Data Among Ethnic Minorities -- 11.1 Introduction -- 11.2 On the Use of the Terms Ethnicity and Ethnic Minorities -- 11.3 On the Representation of Ethnic Minorities in Surveys -- 11.3.1 Coverage of Ethnic Minorities -- 11.3.2 Factors Affecting Nonresponse Among Ethnic Minorities -- 11.3.3 Postsurvey Adjustment Issues Related to Surveys Among Ethnic Minorities -- 11.4 Measurement Issues -- 11.4.1 The Tradeoff When Using Response-Enhancing Measures -- 11.5 Comparability, Timeliness, and Cost Concerns -- 11.5.1 Comparability -- 11.5.2 Timeliness and Cost Considerations -- 11.6 Conclusion -- References -- Section 3 Data Collection and Data Processing Applications -- Chapter 12 Measurement Error in Survey Operations Management: Detection, Quantification, Visualization, and Reduction -- 12.1 TSE Background on Survey Operations -- 12.2 Better and Better: Using Behavior Coding (CARIcode) and Paradata to Evaluate and Improve Question (Specification) Erro... -- 12.2.1 CARI Coding at Westat -- 12.2.2 CARI Experiments -- 12.3 Field-Centered Design: Mobile App for Rapid Reporting and Management -- 12.3.1 Mobile App Case Study -- 12.3.2 Paradata Quality -- 12.4 Faster and Cheaper: Detecting Falsification With GIS Tools -- 12.5 Putting It All Together: Field Supervisor Dashboards -- 12.5.1 Dashboards in Operations -- 12.5.2 Survey Research Dashboards
    Additional Edition: Print version Biemer, Paul P. Total Survey Error in Practice Newark : John Wiley & Sons, Incorporated,c2017 ISBN 9781119041672
    Language: English
    Keywords: Electronic books ; Electronic books
    URL: FULL  ((OIS Credentials Required))
    URL: FULL  ((OIS Credentials Required))
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  • 8
    UID:
    gbv_870009788
    Format: xxvii, 593 Seiten , Illustrationen, Diagramme
    ISBN: 9781119041672
    Series Statement: Wiley series in survey methodology
    Note: Includes bibligraphical references and index
    Additional Edition: ISBN 9781119041696
    Additional Edition: Erscheint auch als Online-Ausgabe Total survey error in practice Hoboken, New Jersey : Wiley, 2017 ISBN 9781119041689
    Additional Edition: ISBN 1119041686
    Additional Edition: ISBN 9781119041702
    Additional Edition: ISBN 1119041708
    Additional Edition: Erscheint auch als Online-Ausgabe Total survey error in practice Hoboken, New Jersey : Wiley, 2017 ISBN 9781119041689
    Language: English
    Subjects: Sociology
    RVK:
    Keywords: Demoskopie ; Umfrage ; Fehler ; Qualität ; Empirische Sozialforschung
    URL: Cover
    Author information: Kreuter, Frauke
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  • 9
    UID:
    gbv_1664939431
    Format: xxix, 510 Seiten , Diagramme , 26 cm
    ISBN: 9781119083740
    Series Statement: Wiley series in survey methodology
    Content: Probability survey-based experimentation and the balancing of internal and external validity concerns -- Within-household selection methods: a critical review and experimental examination -- Measuring within-household contamination: the challenge of interviewing more than one member of a household.
    Content: "With a recent increase of experiments in survey research and methodology, survey researchers have found a need to bring together the many types of experiments used by survey researchers and their applications throughout various disciplines. This book bridges the gap in literature and explores the broad range of experimental design in survey-based experiments with a combined methodological and substantive focus on the ways the experiments are conducted and used in survey research. The book is edited by a group of established experts in the field of survey research/methodology and the chapters feature expert contributors across a variety of disciplines in the social and behavioral sciences. The book approaches coverage on survey-based experiments with a Total Survey Error (TSE) perspective, which provides insight on the strengths and weaknesses of the technique. Using the same basic structure, each chapter starts with a description of the experimental method or application, followed by a reference to any relevant reviews in current literature"--
    Content: "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 bridges the gap in literature and explores the broad range of experimental designs in experiments that use 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 Assignment with Random Probability Sampling 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 ...
    Additional Edition: ISBN 9781119083757
    Additional Edition: ISBN 9781119083764
    Additional Edition: Erscheint auch als Online-Ausgabe Experimental methods in survey research Hoboken, NJ : Wiley, 2019 ISBN 9781119083771
    Additional Edition: ISBN 9781119083757
    Additional Edition: ISBN 9781119083764
    Additional Edition: Erscheint auch als Online-Ausgabe Experimental methods in survey research Hoboken, NJ : Wiley, 2019 ISBN 9781119083771
    Additional Edition: ISBN 9781119083764
    Additional Edition: ISBN 9781119083757
    Language: English
    Keywords: Demoskopie ; Experiment ; Methode ; Demoskopie ; Zufallsauswahl ; Umfrage ; Randomisierung ; Aufsatzsammlung
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  • 10
    UID:
    almahu_BV042075489
    Format: XXV, 414 S. : , graph. Darst.
    Edition: 2. ed.
    ISBN: 978-1-4665-6099-4
    Series Statement: A Chapman & Hall Book
    Language: English
    Subjects: Computer Science , Economics , Psychology
    RVK:
    RVK:
    RVK:
    Keywords: Lineares Modell ; Gemischtes Modell ; Software
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