Details

Autor(en) / Beteiligte

• Lynn, Peter,

Titel

Advances in longitudinal survey methodology

Ort / Verlag

Hoboken, New Jersey : Wiley,

Erscheinungsjahr

[2021]

Beschreibungen/Notizen

• Cover -- Wiley Series in Probability and Statistics -- Title Page -- Copyright -- Contents -- List of Contributors -- Preface -- About the Companion Website -- Chapter 1 Refreshment Sampling for Longitudinal Surveys -- 1.1 Introduction -- 1.2 Principles -- 1.3 Sampling -- 1.3.1 Sampling Frame -- 1.3.2 Screening -- 1.3.3 Sample Design -- 1.3.4 Questionnaire Design -- 1.3.5 Frequency -- 1.4 Recruitment -- 1.5 Data Integration -- 1.6 Weighting -- 1.7 Impact on Analysis -- 1.8 Conclusions -- References -- Chapter 2 Collecting Biomarker Data in Longitudinal Surveys -- 2.1 Introduction -- 2.2 What Are Biomarkers, and Why Are They of Value? -- 2.2.1 Detailed Measurements of Ill Health -- 2.2.2 Biological Pathways -- 2.2.3 Genetics in Longitudinal Studies -- 2.3 Approaches to Collecting Biomarker Data in Longitudinal Studies -- 2.3.1 Consistency and Relevance of Measures Over Time -- 2.3.2 Panel Conditioning and Feedback -- 2.3.3 Choices of When and Who to Ask for Sensitive or Invasive Measures -- 2.3.4 Cost -- 2.4 The Future -- References -- Chapter 3 Innovations in Participant Engagement and Tracking in Longitudinal Surveys -- 3.1 Introduction and Background -- 3.2 Literature Review -- 3.3 Current Practice -- 3.4 New Evidence on Internet and Social Media for Participant Engagement -- 3.4.1 Background -- 3.4.2 Findings -- 3.4.2.1 MCS -- 3.4.2.2 Next Steps -- 3.4.3 Summary and Conclusions -- 3.5 New Evidence on Internet and Social Media for Tracking -- 3.5.1 Background -- 3.5.2 Findings -- 3.5.3 Summary and Conclusions -- 3.6 New Evidence on Administrative Data for Tracking -- 3.6.1 Background -- 3.6.2 Findings -- 3.6.3 Summary and Conclusions -- 3.7 Conclusion -- Acknowledgements -- References -- Chapter 4 Effects on Panel Attrition and Fieldwork Outcomes from Selection for a Supplemental Study: Evidence from the Panel Study of Income Dynamics.
• 4.1 Introduction -- 4.2 Conceptual Framework -- 4.3 Previous Research -- 4.4 Data and Methods -- 4.5 Results -- 4.6 Conclusions -- Acknowledgements -- References -- Chapter 5 The Effects of Biological Data Collection in Longitudinal Surveys on Subsequent Wave Cooperation -- 5.1 Introduction -- 5.2 Literature Review -- 5.3 Biological Data Collection and Subsequent Cooperation: Research Questions -- 5.4 Data -- 5.5 Modelling Steps -- 5.6 Results -- 5.7 Discussion and Conclusion -- 5.8 Implications for Survey Researchers -- References -- Chapter 6 Understanding Data Linkage Consent in Longitudinal Surveys -- 6.1 Introduction -- 6.2 Quantitative Research: Consistency of Consent and Effect of Mode of Data Collection -- 6.2.1 Data and Methods -- 6.2.2 Results -- 6.2.2.1 How Consistent Are Respondents about Giving Consent to Data Linkage between Topics? -- 6.2.2.2 How Consistent Are Respondents about Giving Consent to Data Linkage over Time? -- 6.2.2.3 Does Consistency over Time Vary between Domains? -- 6.2.2.4 What Is the Effect of Survey Mode on Consent? -- 6.3 Qualitative Research: How Do Respondents Decide Whether to Give Consent to Linkage? -- 6.3.1 Methods -- 6.3.2 Results -- 6.3.2.1 How Do Participants Interpret Consent Questions? -- 6.3.2.2 What Do Participants Think Are the Implications of Giving Consent to Linkage? -- 6.3.2.3 What Influences the Participant's Decision Whether or Not to Give Consent? -- 6.3.2.4 How Does the Survey Mode Influence the Decision to Consent? -- 6.3.2.5 Why Do Participants Change their Consent Decision over Time? -- 6.4 Discussion -- Acknowledgements -- References -- Chapter 7 Determinants of Consent to Administrative Records Linkage in Longitudinal Surveys: Evidence from Next Steps -- 7.1 Introduction -- 7.2 Literature Review -- 7.3 Data and Methods -- 7.3.1 About the Study -- 7.3.2 Consents Sought and Consent Procedure.
• 7.3.3 Analytic Sample -- 7.3.4 Methods -- 7.4 Results -- 7.4.1 Consent Rates -- 7.4.2 Regression Models -- 7.4.2.1 Concepts and Variables -- 7.4.2.2 Characteristics Related to All or Most Consent Domains -- 7.4.2.3 National Health Service (NHS) Records -- 7.4.2.4 Police National Computer (PNC) Criminal Records -- 7.4.2.5 Education Records -- 7.4.2.6 Economic Records -- 7.5 Discussion -- 7.5.1 Summary of Results -- 7.5.2 Methodological Considerations and Limitations -- 7.5.3 Practical Implications -- References -- Chapter 8 Consent to Data Linkage: Experimental Evidence from an Online Panel -- 8.1 Introduction -- 8.2 Background -- 8.2.1 Experimental Studies of Data Linkage Consent in Longitudinal Surveys -- 8.3 Research Questions -- 8.4 Method -- 8.4.1 Data -- 8.4.2 Study 1: Attrition Following Data Linkage Consent -- 8.4.3 Study 2: Testing the Effect of Type and Length of Data Linkage Consent Questions -- 8.5 Results -- 8.5.1 Do Requests for Data Linkage Consent Affect Response Rates in Subsequent Waves? (RQ1) -- 8.5.2 Do Consent Rates Depend on Type of Data Linkage Requested? (RQ2a) -- 8.5.3 Do Consent Rates Depend on Survey Mode? (RQ2b) -- 8.5.4 Do Consent Rates Depend on the Length of the Request? (RQ2c) -- 8.5.5 Effects on Understanding of the Data Linkage Process (RQ3) -- 8.5.6 Effects on Perceptions of the Risk of Data Linkage (RQ4) -- 8.6 Discussion -- References -- Chapter 9 Mixing Modes in Household Panel Surveys: Recent Developments and New Findings -- 9.1 Introduction -- 9.2 The Challenges of Mixing Modes in Household Panel Surveys -- 9.3 Current Experiences with Mixing Modes in Longitudinal Household Panels -- 9.3.1 The German Socio‐Economic Panel (SOEP) -- 9.3.2 The Household, Income, and Labour Dynamics in Australia (HILDA) Survey -- 9.3.3 The Panel Study of Income Dynamics (PSID) -- 9.3.4 The UK Household Longitudinal Study (UKHLS).
• 9.3.5 The Korean Labour and Income Panel Study (KLIPS) -- 9.3.6 The Swiss Household Panel (SHP) -- 9.4 The Mixed‐Mode Pilot of the Swiss Household Panel Study -- 9.4.1 Design of the SHP Pilot -- 9.4.2 Results of the First Wave -- 9.4.2.1 Overall Response Rates in the Three Groups -- 9.4.2.2 Use of Different Modes in the Three Groups -- 9.4.2.3 Household Nonresponse in the Three Groups -- 9.4.2.4 Individual Nonresponse in the Three Groups -- 9.5 Conclusion -- References -- Chapter 10 Estimating the Measurement Effects of Mixed Modes in Longitudinal Studies: Current Practice and Issues -- 10.1 Introduction -- 10.2 Types of Mixed‐Mode Designs -- 10.3 Mode Effects and Longitudinal Data -- 10.3.1 Estimating Change from Mixed‐Mode Longitudinal Survey Data -- 10.3.2 General Concepts in the Investigation of Mode Effects -- 10.3.3 Mode Effects on Measurement in Longitudinal Data: Literature Review -- 10.4 Methods for Estimating Mode Effects on Measurement in Longitudinal Studies -- 10.5 Using Structural Equation Modelling to Investigate Mode Differences in Measurement -- 10.6 Conclusion -- Acknowledgement -- References -- Chapter 11 Measuring Cognition in a Multi‐Mode Context -- 11.1 Introduction -- 11.2 Motivation and Previous Literature -- 11.2.1 Measurement of Cognition in Surveys -- 11.2.2 Mode Effects and Survey Response -- 11.2.3 Cognition in a Multi‐Mode Context -- 11.2.4 Existing Mode Comparisons of Cognitive Ability -- 11.3 Data and Methods -- 11.3.1 Data Source -- 11.3.2 Analytic Sample -- 11.3.3 Administration of Cognitive Tests -- 11.3.4 Methods -- 11.3.4.1 Item Missing Data -- 11.3.4.2 Completion Time -- 11.3.4.3 Overall Differences in Scores -- 11.3.4.4 Correlations Between Measures -- 11.3.4.5 Trajectories over Time -- 11.3.4.6 Models Predicting Cognition as an Outcome -- 11.4 Results -- 11.4.1 Item‐Missing Data -- 11.4.2 Completion Time.
• 11.4.3 Differences in Mean Scores -- 11.4.4 Correlations Between Measures -- 11.4.5 Trajectories over Time -- 11.4.6 Substantive Models -- 11.5 Discussion -- Acknowledgements -- References -- Chapter 12 Panel Conditioning: Types, Causes, and Empirical Evidence of What We Know So Far -- 12.1 Introduction -- 12.2 Methods for Studying Panel Conditioning -- 12.3 Mechanisms of Panel Conditioning -- 12.3.1 Survey Response Process and the Effects of Repeated Interviewing -- 12.3.2 Reflection/Cognitive Stimulus -- 12.3.3 Empirical Evidence of Reflection/Cognitive Stimulus -- 12.3.3.1 Changes in Attitudes Due to Reflection -- 12.3.3.2 Changes in (Self‐Reported) Behaviour Due to Reflection -- 12.3.3.3 Changes in Knowledge Due to Reflection -- 12.3.4 Social Desirability Reduction -- 12.3.5 Empirical Evidence of Social Desirability Effects -- 12.3.6 Satisficing -- 12.3.7 Empirical Evidence of Satisficing -- 12.3.7.1 Misreporting to Filter Questions as a Conditioning Effect Due to Satisficing -- 12.3.7.2 Misreporting to More Complex Filter (Looping) Questions -- 12.3.7.3 Within‐Interview and Between‐Waves Conditioning in Filter Questions -- 12.4 Conclusion and Implications for Survey Practice -- References -- Chapter 13 Interviewer Effects in Panel Surveys -- 13.1 Introduction -- 13.2 Motivation and State of Research -- 13.2.1 Sources of Interviewer‐Related Measurement Error -- 13.2.1.1 Interviewer Deviations -- 13.2.1.2 Social Desirability -- 13.2.1.3 Priming -- 13.2.2 Moderating Factors of Interviewer Effects -- 13.2.3 Interviewer Effects in Panel Surveys -- 13.2.4 Identifying Interviewer Effects -- 13.2.4.1 Interviewer Variance -- 13.2.4.2 Interviewer Bias -- 13.2.4.3 Using Panel Data to Identify Interviewer Effects -- 13.3 Data -- 13.3.1 The Socio‐Economic Panel -- 13.3.2 Variables -- 13.4 The Size and Direction of Interviewer Effects in Panels.
• 13.4.1 Methods.
• "The methodology of longitudinal surveys is a specialist topic which has evolved from the field of survey methodology. Survey methodology itself has evolved over the last century or so, with an early focus on sampling theory (1890s to 1940s), followed by attention to question and questionnaire design (1940s to 1970s) and obtaining respondent participation (1980s to 2000s). More recent developments included web survey methods and mixed mode methods, other uses of new technologies, data linkage, the use of paradata. Though the first longitudinal surveys began in the 1960s, such surveys were rare until the 1980s. Researchers became increasingly aware of various unique features and opportunities of longitudinal surveys and methodological research into these unique features developed rapidly throughout the 1990s and 2000s. The data produced by longitudinal surveys allow researchers to better understand dynamic processes of change, including processes of cause-and-effect, that can barely be addressed by data from cross-sectional surveys. An understanding of the implications of the methodological options available for the design and implementation of such surveys will help researchers to produce better longitudinal data in future."--
• Description based on print version record.