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MARC Lista (tabellare)
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Mostreig (Estadística)
Anàlisi de regressió
Estadística matemàtica
Models lineals (Estadística)
Metodologia de la ciència
Soggetto genere / forma Llibres electrònics
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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  
Washington, DC : , : World Bank Group, , [2018]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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  
Washington, D.C. : , : The World Bank, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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
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Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2003
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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
Opac: Controlla la disponibilità qui