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Administrative records for survey methodology / / editors, Asaph Young Chun [et al.]
| Administrative records for survey methodology / / editors, Asaph Young Chun [et al.] |
| Pubbl/distr/stampa | Hoboken, NJ : , : Wiley, , [2021] |
| Descrizione fisica | 1 online resource (xxv, 354 pages) : illustrations (some color) |
| Disciplina | 001.433 |
| Collana | Wiley Series in Survey Methodology |
| Soggetto topico |
Surveys - Methodology
Surveys - Quality control |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-27206-8
1-119-27205-X 1-119-27207-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910555131103321 |
| Hoboken, NJ : , : Wiley, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Administrative records for survey methodology / / editors, Asaph Young Chun [et al.]
| Administrative records for survey methodology / / editors, Asaph Young Chun [et al.] |
| Pubbl/distr/stampa | Hoboken, NJ : , : Wiley, , [2021] |
| Descrizione fisica | 1 online resource (xxv, 354 pages) : illustrations (some color) |
| Disciplina | 001.433 |
| Collana | Wiley Series in Survey Methodology |
| Soggetto topico |
Surveys - Methodology
Surveys - Quality control |
| ISBN |
1-119-27206-8
1-119-27205-X 1-119-27207-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910830909303321 |
| Hoboken, NJ : , : Wiley, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced Modeling and Data Challenges / / by Mike Nguyen
| Advanced Modeling and Data Challenges / / by Mike Nguyen |
| Autore | Nguyen Mike |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (417 pages) |
| Disciplina | 001.433 |
| Collana | Mathematics and Statistics Series |
| Soggetto topico |
Sampling (Statistics)
Regression analysis Mathematical statistics Methodology of Data Collection and Processing Linear Models and Regression Parametric Inference |
| ISBN |
9783032017192
9783032017185 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9911039319003321 |
Nguyen Mike
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in longitudinal survey methodology / / edited by Peter Lynn
| Advances in longitudinal survey methodology / / edited by Peter Lynn |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2021] |
| Descrizione fisica | 1 online resource (xxvii, 516 pages) : illustrations |
| Disciplina | 001.433 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico | Longitudinal method |
| ISBN |
1-119-37695-5
1-119-37694-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910555113403321 |
| Hoboken, New Jersey : , : Wiley, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in longitudinal survey methodology / / edited by Peter Lynn
| Advances in longitudinal survey methodology / / edited by Peter Lynn |
| Pubbl/distr/stampa | John Wiley & Sons, Ltd |
| Descrizione fisica | 1 online resource (xxvii, 516 pages) : illustrations |
| Disciplina | 001.433 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico | Longitudinal method |
| ISBN |
1-119-37696-3
1-119-37695-5 1-119-37694-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910830784303321 |
| John Wiley & Sons, Ltd | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The analysis of household surveys : a microeconometric approach to development policy / / Angus Deaton
| The analysis of household surveys : a microeconometric approach to development policy / / Angus Deaton |
| Autore | Deaton Angus |
| Edizione | [Reissue edition with a new preface.] |
| Pubbl/distr/stampa | Washington, DC : , : World Bank Group, , [2018] |
| Descrizione fisica | 1 online resource (496 pages) |
| Disciplina | 001.433 |
| Soggetto topico | Household surveys - Developing countries - Methodology |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-4648-1352-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910511804703321 |
|
Deaton Angus
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||
| Washington, DC : , : World Bank Group, , [2018] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The Analysis of Household Surveys (Reissue Edition with a New Preface) : : A Microeconometric Approach to Development Policy / / Angus Deaton
| The Analysis of Household Surveys (Reissue Edition with a New Preface) : : A Microeconometric Approach to Development Policy / / Angus Deaton |
| Autore | Deaton Angus |
| Edizione | [Reissue edition with a new preface.] |
| Pubbl/distr/stampa | Washington, D.C. : , : The World Bank, , 2019 |
| Descrizione fisica | 1 online resource (494 pages) |
| Disciplina | 001.433 |
| Altri autori (Persone) | DeatonAngus |
| Soggetto topico | Household surveys - Developing countries - Methodology |
| ISBN | 1-4648-1352-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910793304203321 |
|
Deaton Angus
|
||
| Washington, D.C. : , : The World Bank, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The Analysis of Household Surveys (Reissue Edition with a New Preface) : : A Microeconometric Approach to Development Policy / / Angus Deaton
| The Analysis of Household Surveys (Reissue Edition with a New Preface) : : A Microeconometric Approach to Development Policy / / Angus Deaton |
| Autore | Deaton Angus |
| Edizione | [Reissue edition with a new preface.] |
| Pubbl/distr/stampa | Washington, D.C. : , : The World Bank, , 2019 |
| Descrizione fisica | 1 online resource (494 pages) |
| Disciplina | 001.433 |
| Altri autori (Persone) | DeatonAngus |
| Soggetto topico | Household surveys - Developing countries - Methodology |
| ISBN |
9781464813528
1464813523 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910954960803321 |
|
Deaton Angus
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||
| Washington, D.C. : , : The World Bank, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analysis of survey data [[electronic resource] /] / edited by R.L. Chambers and C.J. Skinner
| Analysis of survey data [[electronic resource] /] / edited by R.L. Chambers and C.J. Skinner |
| Pubbl/distr/stampa | Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 |
| Descrizione fisica | 1 online resource (399 p.) |
| Disciplina |
001.4/22
001.433 |
| Altri autori (Persone) |
ChambersR. L (Ray L.)
SkinnerC. J |
| Collana | Wiley series in survey methodology |
| Soggetto topico | Mathematical statistics - Methodology |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-27189-2
9786610271894 0-470-32742-1 0-470-86439-7 0-470-86720-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analysis of Survey Data; Contents; Preface; List of Contributors; Chapter 1 Introduction; 1.1. The analysis of survey data; 1.2. Framework, terminology and specification of parameters; 1.3. Statistical inference; 1.4. Relation to Skinner, Holt and Smith (1989); 1.5. Outline of this book; PART A APPROACHES TO INFERENCE; Chapter 2 Introduction to Part A; 2.1. Introduction; 2.2. Full information likelihood; 2.3. Sample likelihood; 2.4. Pseudo-likelihood; 2.5. Pseudo-likelihood applied to analytic inference; 2.6. Bayesian inference for sample surveys
2.7. Application of the likelihood principle in descriptive inferenceChapter 3 Design-based and Model-based Methods for Estimating Model Parameters; 3.1. Choice of methods; 3.2. Design-based and model-based linear estimators; 3.2.1. Parameters of interest; 3.2.2. Linear estimators; 3.2.3. Properties of b and b; 3.3. Design-based and total variances of linear estimators; 3.3.1. Design-based and total variance of b; 3.3.2. Design-based mean squared error of b and its model expectation; 3.4. More complex estimators; 3.4.1. Taylor linearisation of non-linear statistics; 3.4.2. Ratio estimation 3.4.3. Non-linear statistics - explicitly defined statistics3.4.4. Non-linear statistics - defined implicitly by score statistics; 3.4.5. Total variance matrix of b for non-negligible sampling fractions; 3.5. Conditional model-based properties; 3.5.1. Conditional model-based properties of b; 3.5.2. Conditional model-based expectations; 3.5.3. Conditional model-based variance for b and the use of estimating functions; 3.6. Properties of methods when the assumed model is invalid; 3.6.1. Critical model assumptions; 3.6.2. Model-based properties of b; 3.6.3. Model-based properties of b 3.6.4. Summary3.7. Conclusion; Chapter 4 The Bayesian Approach to Sample Survey Inference; 4.1. Introduction; 4.2. Modeling the selection mechanism; Chapter 5 Interpreting a Sample as Evidence about a Finite Population; 5.1. Introduction; 5.2. The evidence in a sample from a finite population; 5.2.1. Evidence about a probability; 5.2.2. Evidence about a population proportion; 5.2.3. The likelihood function for a population proportion or total; 5.2.4. The probability of misleading evidence; 5.2.5. Evidence about the average count in a finite population 5.2.6. Evidence about a population mean under a regression model5.3. Defining the likelihood function for a finite population; PART B CATEGORICAL RESPONSE DATA; Chapter 6 Introduction to Part B; 6.1. Introduction; 6.2. Analysis of tabular data; 6.2.1. One-way classification; 6.2.2. Multi-way classifications and log-linear models; 6.2.3. Logistic models for domain proportions; 6.3. Analysis of unit-level data; 6.3.1. Logistic regression; 6.3.2. Some issues in weighting; Chapter 7 Analysis of Categorical Response Data from Complex Surveys: an Appraisal and Update; 7.1. Introduction 7.2. Fitting and testing log-linear models |
| Record Nr. | UNINA-9910143508403321 |
| Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analysis of survey data [[electronic resource] /] / edited by R.L. Chambers and C.J. Skinner
| Analysis of survey data [[electronic resource] /] / edited by R.L. Chambers and C.J. Skinner |
| Pubbl/distr/stampa | Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 |
| Descrizione fisica | 1 online resource (399 p.) |
| Disciplina |
001.4/22
001.433 |
| Altri autori (Persone) |
ChambersR. L (Ray L.)
SkinnerC. J |
| Collana | Wiley series in survey methodology |
| Soggetto topico | Mathematical statistics - Methodology |
| ISBN |
1-280-27189-2
9786610271894 0-470-32742-1 0-470-86439-7 0-470-86720-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Analysis of Survey Data; Contents; Preface; List of Contributors; Chapter 1 Introduction; 1.1. The analysis of survey data; 1.2. Framework, terminology and specification of parameters; 1.3. Statistical inference; 1.4. Relation to Skinner, Holt and Smith (1989); 1.5. Outline of this book; PART A APPROACHES TO INFERENCE; Chapter 2 Introduction to Part A; 2.1. Introduction; 2.2. Full information likelihood; 2.3. Sample likelihood; 2.4. Pseudo-likelihood; 2.5. Pseudo-likelihood applied to analytic inference; 2.6. Bayesian inference for sample surveys
2.7. Application of the likelihood principle in descriptive inferenceChapter 3 Design-based and Model-based Methods for Estimating Model Parameters; 3.1. Choice of methods; 3.2. Design-based and model-based linear estimators; 3.2.1. Parameters of interest; 3.2.2. Linear estimators; 3.2.3. Properties of b and b; 3.3. Design-based and total variances of linear estimators; 3.3.1. Design-based and total variance of b; 3.3.2. Design-based mean squared error of b and its model expectation; 3.4. More complex estimators; 3.4.1. Taylor linearisation of non-linear statistics; 3.4.2. Ratio estimation 3.4.3. Non-linear statistics - explicitly defined statistics3.4.4. Non-linear statistics - defined implicitly by score statistics; 3.4.5. Total variance matrix of b for non-negligible sampling fractions; 3.5. Conditional model-based properties; 3.5.1. Conditional model-based properties of b; 3.5.2. Conditional model-based expectations; 3.5.3. Conditional model-based variance for b and the use of estimating functions; 3.6. Properties of methods when the assumed model is invalid; 3.6.1. Critical model assumptions; 3.6.2. Model-based properties of b; 3.6.3. Model-based properties of b 3.6.4. Summary3.7. Conclusion; Chapter 4 The Bayesian Approach to Sample Survey Inference; 4.1. Introduction; 4.2. Modeling the selection mechanism; Chapter 5 Interpreting a Sample as Evidence about a Finite Population; 5.1. Introduction; 5.2. The evidence in a sample from a finite population; 5.2.1. Evidence about a probability; 5.2.2. Evidence about a population proportion; 5.2.3. The likelihood function for a population proportion or total; 5.2.4. The probability of misleading evidence; 5.2.5. Evidence about the average count in a finite population 5.2.6. Evidence about a population mean under a regression model5.3. Defining the likelihood function for a finite population; PART B CATEGORICAL RESPONSE DATA; Chapter 6 Introduction to Part B; 6.1. Introduction; 6.2. Analysis of tabular data; 6.2.1. One-way classification; 6.2.2. Multi-way classifications and log-linear models; 6.2.3. Logistic models for domain proportions; 6.3. Analysis of unit-level data; 6.3.1. Logistic regression; 6.3.2. Some issues in weighting; Chapter 7 Analysis of Categorical Response Data from Complex Surveys: an Appraisal and Update; 7.1. Introduction 7.2. Fitting and testing log-linear models |
| Record Nr. | UNINA-9910830716603321 |
| Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
