05357nam 2200721 a 450 991014125970332120230801223456.01-118-35887-21-280-87995-597866137212661-118-35880-51-118-35888-01-118-35943-7(CKB)2670000000208518(EBL)954614(OCoLC)798536286(SSID)ssj0000676769(PQKBManifestationID)11474980(PQKBTitleCode)TC0000676769(PQKBWorkID)10683649(PQKB)10317098(MiAaPQ)EBC954614(DLC) 2012018371(Au-PeEL)EBL954614(CaPaEBR)ebr10579514(CaONFJC)MIL372126(EXLCZ)99267000000020851820120503d2012 uy 0engurcn|||||||||txtccrBasic and advanced Bayesian structural equation modeling[electronic resource] with applications in the medical and behavioral sciences /Sik-Yum Lee and Xin-Yuan SongHoboken Wiley20121 online resource (397 p.)Wiley series in probability and statisticsDescription based upon print version of record.0-470-66952-7 Includes bibliographical references and index.Basic and Advanced Bayesian Structural Equation Modeling; Contents; About the authors; Preface; 1 Introduction; 1.1 Observed and latent variables; 1.2 Structural equation model; 1.3 Objectives of the book; 1.4 The Bayesian approach; 1.5 Real data sets and notation; Appendix 1.1: Information on real data sets; References; 2 Basic concepts and applications of structural equation models; 2.1 Introduction; 2.2 Linear SEMs; 2.2.1 Measurement equation; 2.2.2 Structural equation and one extension; 2.2.3 Assumptions of linear SEMs; 2.2.4 Model identification; 2.2.5 Path diagram2.3 SEMs with fixed covariates 2.3.1 The model; 2.3.2 An artificial example; 2.4 Nonlinear SEMs; 2.4.1 Basic nonlinear SEMs; 2.4.2 Nonlinear SEMs with fixed covariates; 2.4.3 Remarks; 2.5 Discussion and conclusions; References; 3 Bayesian methods for estimating structural equation models; 3.1 Introduction; 3.2 Basic concepts of the Bayesian estimation and prior distributions; 3.2.1 Prior distributions; 3.2.2 Conjugate prior distributions in Bayesian analyses of SEMs; 3.3 Posterior analysis using Markov chain Monte Carlo methods; 3.4 Application of Markov chain Monte Carlo methods3.5 Bayesian estimation via WinBUGS Appendix 3.1: The gamma, inverted gamma, Wishart, and inverted Wishart distributions and their characteristics; Appendix 3.2: The Metropolis-Hastings algorithm; Appendix 3.3: Conditional distributions [Ω|Y,θ] and [θ|Y,Ω]; Appendix 3.4: Conditional distributions [Ω|Y,θ] and [θ|Y,Ω] in nonlinear SEMs with covariates; Appendix 3.5: WinBUGS code; Appendix 3.6: R2WinBUGS code; References; 4 Bayesian model comparison and model checking; 4.1 Introduction; 4.2 Bayes factor; 4.2.1 Path sampling; 4.2.2 A simulation study; 4.3 Other model comparison statistics4.3.1 Bayesian information criterion and Akaike information criterion 4.3.2 Deviance information criterion; 4.3.3 Lν-measure; 4.4 Illustration; 4.5 Goodness of fit and model checking methods; 4.5.1 Posterior predictive p-value; 4.5.2 Residual analysis; Appendix 4.1: WinBUGS code; Appendix 4.2: R code in Bayes factor example; Appendix 4.3: Posterior predictive p-value for model assessment; References; 5 Practical structural equation models; 5.1 Introduction; 5.2 SEMs with continuous and ordered categorical variables; 5.2.1 Introduction; 5.2.2 The basic model; 5.2.3 Bayesian analysis5.2.4 Application: Bayesian analysis of quality of life data 5.2.5 SEMs with dichotomous variables; 5.3 SEMs with variables from exponential family distributions; 5.3.1 Introduction; 5.3.2 The SEM framework with exponential family distributions; 5.3.3 Bayesian inference; 5.3.4 Simulation study; 5.4 SEMs with missing data; 5.4.1 Introduction; 5.4.2 SEMs with missing data that are MAR; 5.4.3 An illustrative example; 5.4.4 Nonlinear SEMs with nonignorable missing data; 5.4.5 An illustrative real exampleAppendix 5.1: Conditional distributions and implementation of the MH algorithm for SEMs with continuous and ordered categorical variables"This book introduces the Bayesian approach to SEMs, including the selection of prior distributions and data augmentation, and offers an overview of the subject's recent advances"--Provided by publisher.Wiley series in probability and statistics.Structural equation modelingBayesian statistical decision theoryStructural equation modeling.Bayesian statistical decision theory.519.5/3MAT029000bisacshLee Sik-Yum308566Song Xin-Yuan891931MiAaPQMiAaPQMiAaPQBOOK9910141259703321Basic and advanced Bayesian structural equation modeling1992023UNINA04008nam 22008653 450 991076581600332120241107093928.0978113454925211345492539781280047619128004761597804152413730415241375978113454926911345492619780203645055020364505710.4324/9780203645055 (CKB)1000000000448451(SSID)ssj0000306125(PQKBManifestationID)11259824(PQKBTitleCode)TC0000306125(PQKBWorkID)10294906(PQKB)10149302(MiAaPQ)EBC200026(OCoLC)252883900(oapen)https://directory.doabooks.org/handle/20.500.12854/38882(MiAaPQ)EBC7245634(Au-PeEL)EBL7245634(OCoLC)1378937141(ODN)ODN0004065376(ScCtBLL)5bef2cca-4cfb-41c6-a0c8-b1a8c5e6f6a3(OCoLC)1135845562(oapen)doab38882(EXLCZ)99100000000044845120231110h20172002 uy 0engurcn|||||||||txtccrPlanning for crime prevention a transatlantic perspective /Richard H. Schneider and Ted Kitchen2004Abingdon, Oxon ;New York, NY :Routledge,2017.©2002xxiv, 331 p. illRTPI library seriesBibliographic Level Mode of Issuance: Monograph0-203-68599-7 0-415-24136-7 Includes bibliographical references and index.Machine generated contents note: PART 1 CONTEXT AND KEY IDEAS 1 -- 01 Crime, costs and the quality of life 3 -- 02 Crime trends in the USA and in Britain 29 -- 03 Echoes from the past: caves, castles, citadels, walls and trenches 65 -- 04 Basic theories and principles of place-based crime prevention planning 91 --PART 2 POLICY AND PRACTICE 119 -- 05 American policy and practice 121 -- 06 Case studies in North America 155 -- 07 British policy and practice 183 -- 08 British case studies 219 --PART 3 COMPARISONS AND KEY ISSUES 259 -- 09 Some Anglo-American comparisons 261 -- 10 The way forward 287.Crime and the fear of crime are issues high in public concern and on political agendas in most developed countries. This book takes these issues and relates them to the contribution that urban planners and participative planning processes can make in response to these problems. Its focus is thus on the extent to which crime opportunities can be prevented or reduced through the design, planning and management of the built environment. The perspective of the book is transatlantic and comparative, not only because ideas and inspiration in this and many other fields increasingly move between countries but also because there is a great deal of relevant theoretical material and practice in both the USA and the UK which has not previously been pulled together in this systemic manner.RTPI library series.Crime preventionUnited StatesCrime preventionGreat BritainCity planningUnited StatesCity planningGreat BritainCrime prevention and architectural designCrime preventionCrime preventionCity planningCity planningCrime prevention and architectural design.364.4/9/0941ARC000000ARC008000bisacshSchneider Richard H(Richard Harold),1947-1357515Kitchen TedMiAaPQMiAaPQMiAaPQBOOK9910765816003321Planning for Crime Prevention3363656UNINA