LEADER 05611nam 2200769Ia 450 001 9910818228803321 005 20200520144314.0 010 $a9786612687860 010 $a9781282687868 010 $a1282687867 010 $a9780470743874 010 $a0470743875 010 $a9780470743911 010 $a0470743913 035 $a(CKB)1000000000715985 035 $a(EBL)416458 035 $a(OCoLC)476248215 035 $a(SSID)ssj0000201867 035 $a(PQKBManifestationID)11168677 035 $a(PQKBTitleCode)TC0000201867 035 $a(PQKBWorkID)10245703 035 $a(PQKB)10932421 035 $a(MiAaPQ)EBC416458 035 $a(Au-PeEL)EBL416458 035 $a(CaPaEBR)ebr10300559 035 $a(CaONFJC)MIL268786 035 $a(Perlego)2764481 035 $a(EXLCZ)991000000000715985 100 $a20090218d2009 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMethodology of longitudinal surveys /$fPeter Lynn 205 $a1st ed. 210 $aChichester, UK $cJohn Wiley & Sons$d2009 215 $a1 online resource (418 p.) 225 1 $aWiley series in survey methodology 300 $aDescription based upon print version of record. 311 08$a9780470018712 311 08$aversion imprimée 0470018712 320 $aIncludes bibliographical references and index. 327 $aMethodology of Longitudinal Surveys; Contents; Preface; 1 Methods for Longitudinal Surveys; 1.1 Introduction; 1.2 Types of Longitudinal Surveys; 1.3 Strengths of Longitudinal Surveys; 1.3.1 Analysis Advantages; 1.3.2 Data Collection Advantages; 1.4 Weaknesses of Longitudinal Surveys; 1.4.1 Analysis Disadvantages; 1.4.2 Data Collection Disadvantages; 1.5 Design Features Specific to Longitudinal Surveys; 1.5.1 Population, Sampling and Weighting; 1.5.2 Other Design Issues; 1.6 Quality in Longitudinal Surveys; 1.6.1 Coverage Error; 1.6.2 Sampling Error; 1.6.3 Non-response Error 327 $a1.6.4 Measurement Error 1.7 Conclusions; References; 2 Sample Design for Longitudinal Surveys; 2.1 Introduction; 2.2 Types of Longitudinal Sample Design; 2.3 Fundamental Aspects of Sample Design; 2.3.1 Defining the Longitudinal Population; 2.3.2 Target Variables; 2.3.3 Sample Size; 2.3.4 Clustering; 2.3.5 Treatment of Movers; 2.3.6 Stratification; 2.3.7 Variances and Design Effects; 2.3.8 Selection Probabilities; 2.4 Other Aspects of Design and Implementation; 2.4.1 Choice of Rotation Period and Pattern; 2.4.2 Dealing with Births (and Deaths); 2.4.3 Sample Overlap 327 $a2.4.4 Stability of Units and Hierarchies 2.5 Conclusion; References; 3 Ethical Issues in Longitudinal Surveys; 3.1 Introduction; 3.2 History of Research Ethics; 3.3 Informed Consent; 3.3.1 Initial Consent; 3.3.2 Continuing Consent; 3.3.3 Consent to Trace Respondents; 3.3.4 Consent for Unanticipated Activities or Analyses; 3.3.5 Implications for Consent of Changing Circumstances of Sample Members; 3.3.6 Consent for Linkage to Administrative Data; 3.3.7 Using Administrative Data without Full Consent; 3.3.8 Can Fully Informed Consent be Realised?; 3.4 Free Choice Regarding Participation 327 $a3.5 Avoiding Harm 3.6 Participant Confidentiality and Data Protection; 3.6.1 Dependent Interviewing; 3.6.2 The Treatment of Research Data; 3.7 Independent Ethical Overview and Participant Involvement; Acknowledgements; References; 4 Enhancing Longitudinal Surveys by Linking to Administrative Data; 4.1 Introduction; 4.2 Administrative Data as a Research Resource; 4.3 Record Linkage Methodology; 4.4 Linking Survey Data with Administrative Data at Individual Level; 4.4.1 Sampling, Sample Maintenance and Sample Evaluation; 4.4.2 Evaluation Methodology 327 $a4.4.3 Supplementing and Validating Survey Data 4.5 Ethical and Legal Issues; 4.5.1 Ethical Issues; 4.5.2 Legal Issues; 4.5.3 Disclosure Control; 4.6 Conclusion; References; 5 Tackling Seam Bias Through Questionnaire Design; 5.1 Introduction; 5.2 Previous Research on Seam Bias; 5.3 SIPP and its Dependent Interviewing Procedures; 5.3.1 SIPP's Pre-2004 Use of DI; 5.3.2 Development of New DI Procedures; 5.3.3 Testing and Refining the New Procedures; 5.4 Seam Bias Comparison - SIPP 2001 and SIPP 2004; 5.4.1 Seam Bias Analysis for Programme Participation and Other 'Spell' Characteristics 327 $a5.4.2 Seam Bias Evaluation for Income Amount Transitions 330 $aLongitudinal surveys are surveys that involve collecting data from multiple subjects on multiple occasions. They are typically used for collecting data relating to social, economic, educational and health-related issues and they serve as an important tool for economists, sociologists, and other researchers. Focusing on the design, implementation and analysis of longitudinal surveys, Methodology of Longitudinal Surveys discusses the current state of the art in carrying out these surveys. The book also covers issues that arise in surveys that collect longitudinal data via retrospective 410 0$aWiley series in survey methodology. 606 $aSocial sciences$vLongitudinal studies 606 $aSurveys$xMethodology 615 0$aSocial sciences 615 0$aSurveys$xMethodology. 676 $a001.4/33 676 $a300.723 686 $aMR 2000$2rvk 686 $aMR 2400$2rvk 700 $aLynn$b Peter$f1966-$01698922 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910818228803321 996 $aMethodology of longitudinal surveys$94080775 997 $aUNINA LEADER 02863nam 22006015 450 001 9910720086203321 005 20251113205434.0 010 $a9789811978678$b(electronic bk.) 010 $z9789811978661 024 7 $a10.1007/978-981-19-7867-8 035 $a(MiAaPQ)EBC7246195 035 $a(Au-PeEL)EBL7246195 035 $a(DE-He213)978-981-19-7867-8 035 $a(OCoLC)1378937627 035 $a(OCoLC)1379200693 035 $a(PPN)270615881 035 $a(CKB)26592054900041 035 $a(EXLCZ)9926592054900041 100 $a20230505d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputer Vision and Machine Intelligence $eProceedings of CVMI 2022 /$fedited by Massimo Tistarelli, Shiv Ram Dubey, Satish Kumar Singh, Xiaoyi Jiang 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (777 pages) 225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v586 311 08$aPrint version: Tistarelli, Massimo Computer Vision and Machine Intelligence Singapore : Springer Singapore Pte. Limited,c2023 9789811978661 327 $aEfficient Voluntary Contact-Tracing System & Network for COVID-19 Patients using Sound Waves and Predictive Analysis using K-Means -- Direct De Novo Molecule Generation using Probabilistic Diverse Variational Autoencoder -- Automated Molecular Subtyping of Breast Cancer Through Immunohistochemistry Image Analysis. 330 $aThis book presents selected research papers on current developments in the fields of computer vision and machine intelligence from International Conference on Computer Vision and Machine Intelligence (CVMI 2022). The book covers topics in image processing, artificial intelligence, machine learning, deep learning, computer vision, machine intelligence, etc. The book is useful for researchers, postgraduate and undergraduate students, and professionals working in this domain. . 410 0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v586 606 $aComputational intelligence 606 $aComputer vision 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aComputer Vision 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aComputer Vision. 615 24$aArtificial Intelligence. 676 $a006.3 700 $aTistarelli$b Massimo$0606107 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910720086203321 996 $aComputer Vision and Machine Intelligence$93418327 997 $aUNINA