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Basic and advanced Bayesian structural equation modeling [[electronic resource] ] : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song
| Basic and advanced Bayesian structural equation modeling [[electronic resource] ] : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song |
| Autore | Lee Sik-Yum |
| Pubbl/distr/stampa | Hoboken, : Wiley, 2012 |
| Descrizione fisica | 1 online resource (397 p.) |
| Disciplina | 519.5/3 |
| Altri autori (Persone) | SongXin-Yuan |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Structural equation modeling
Bayesian statistical decision theory |
| ISBN |
1-118-35887-2
1-280-87995-5 9786613721266 1-118-35880-5 1-118-35888-0 1-118-35943-7 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 diagram
2.3 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 methods 3.5 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 statistics 4.3.1 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 analysis 5.2.4 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 example Appendix 5.1: Conditional distributions and implementation of the MH algorithm for SEMs with continuous and ordered categorical variables |
| Record Nr. | UNINA-9910141259703321 |
Lee Sik-Yum
|
||
| Hoboken, : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Basic and advanced Bayesian structural equation modeling [[electronic resource] ] : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song
| Basic and advanced Bayesian structural equation modeling [[electronic resource] ] : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song |
| Autore | Lee Sik-Yum |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, : Wiley, 2012 |
| Descrizione fisica | 1 online resource (397 p.) |
| Disciplina | 519.5/3 |
| Altri autori (Persone) | SongXin-Yuan |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Structural equation modeling
Bayesian statistical decision theory |
| ISBN |
1-118-35887-2
1-280-87995-5 9786613721266 1-118-35880-5 1-118-35888-0 1-118-35943-7 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 diagram
2.3 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 methods 3.5 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 statistics 4.3.1 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 analysis 5.2.4 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 example Appendix 5.1: Conditional distributions and implementation of the MH algorithm for SEMs with continuous and ordered categorical variables |
| Record Nr. | UNINA-9910821778903321 |
|
Lee Sik-Yum
|
||
| Hoboken, : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Structural equation modeling [[electronic resource] ] : a Bayesian approach / / Sik-Yum Lee
| Structural equation modeling [[electronic resource] ] : a Bayesian approach / / Sik-Yum Lee |
| Autore | Lee Sik-Yum |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : Wiley, c2007 |
| Descrizione fisica | 1 online resource (459 p.) |
| Disciplina |
519.53
519.535 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Structural equation modeling
Bayesian statistical decision theory |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-83855-8
9786610838554 0-470-02473-9 0-470-02424-0 |
| Classificazione | 31.73 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Structural Equation Modeling; Contents; About the Author; Preface; 1 Introduction; 1.1 Standard Structural Equation Models; 1.2 Covariance Structure Analysis; 1.3 Why a New Book?; 1.4 Objectives of the Book; 1.5 Data Sets and Notations; Appendix 1.1; References; 2 Some Basic Structural Equation Models; 2.1 Introduction; 2.2 Exploratory Factor Analysis; 2.3 Confirmatory and Higher-order Factor Analysis Models; 2.4 The LISREL Model; 2.5 The Bentler-Weeks Model; 2.6 Discussion; References; 3 Covariance Structure Analysis; 3.1 Introduction; 3.2 Definitions, Notations and Preliminary Results
3.3 GLS Analysis of Covariance Structure3.4 ML Analysis of Covariance Structure; 3.5 Asymptotically Distribution-free Methods; 3.6 Some Iterative Procedures; Appendix 3.1: Matrix Calculus; Appendix 3.2: Some Basic Results in Probability Theory; Appendix 3.3: Proofs of Some Results; References; 4 Bayesian Estimation of Structural Equation Models; 4.1 Introduction; 4.2 Basic Principles and Concepts of Bayesian Analysis of SEMs; 4.3 Bayesian Estimation of the CFA Model; 4.4 Bayesian Estimation of Standard SEMs; 4.5 Bayesian Estimation via WinBUGS; Appendix 4.1: The Metropolis-Hastings Algorithm 6.3 Bayesian Estimation and Goodness-of-fit6.4 Bayesian Model Comparison; 6.5 Application 1: Bayesian Selection of the Number of Factors in EFA; 6.6 Application 2: Bayesian Analysis of Quality of Life Data; References; 7 Structural Equation Models with Dichotomous Variables; 7.1 Introduction; 7.2 Bayesian Analysis; 7.3 Analysis of a Multivariate Probit Confirmatory Factor Analysis Model; 7.4 Discussion; Appendix 7.1: Questions Associated with the Manifest Variables; References; 8 Nonlinear Structural Equation Models; 8.1 Introduction; 8.2 Bayesian Analysis of a Nonlinear SEM 8.3 Bayesian Estimation of Nonlinear SEMs with Mixed Continuous and Ordered Categorical Variables8.4 Bayesian Estimation of SEMs with Nonlinear Covariates and Latent Variables; 8.5 Bayesian Model Comparison; References; 9 Two-level Nonlinear Structural Equation Models; 9.1 Introduction; 9.2 A Two-level Nonlinear SEM with Mixed Type Variables; 9.3 Bayesian Estimation; 9.4 Goodness-of-fit and Model Comparison; 9.5 An Application: Filipina CSWs Study; 9.6 Two-level Nonlinear SEMs with Cross-level Effects; 9.7 Analysis of Two-level Nonlinear SEMs using WinBUGS Appendix 9.1: Conditional Distributions: Two-level Nonlinear SEM |
| Record Nr. | UNINA-9910143581603321 |
|
Lee Sik-Yum
|
||
| Chichester, England ; ; Hoboken, NJ, : Wiley, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Structural equation modeling [[electronic resource] ] : a Bayesian approach / / Sik-Yum Lee
| Structural equation modeling [[electronic resource] ] : a Bayesian approach / / Sik-Yum Lee |
| Autore | Lee Sik-Yum |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : Wiley, c2007 |
| Descrizione fisica | 1 online resource (459 p.) |
| Disciplina |
519.53
519.535 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Structural equation modeling
Bayesian statistical decision theory |
| ISBN |
1-280-83855-8
9786610838554 0-470-02473-9 0-470-02424-0 |
| Classificazione | 31.73 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Structural Equation Modeling; Contents; About the Author; Preface; 1 Introduction; 1.1 Standard Structural Equation Models; 1.2 Covariance Structure Analysis; 1.3 Why a New Book?; 1.4 Objectives of the Book; 1.5 Data Sets and Notations; Appendix 1.1; References; 2 Some Basic Structural Equation Models; 2.1 Introduction; 2.2 Exploratory Factor Analysis; 2.3 Confirmatory and Higher-order Factor Analysis Models; 2.4 The LISREL Model; 2.5 The Bentler-Weeks Model; 2.6 Discussion; References; 3 Covariance Structure Analysis; 3.1 Introduction; 3.2 Definitions, Notations and Preliminary Results
3.3 GLS Analysis of Covariance Structure3.4 ML Analysis of Covariance Structure; 3.5 Asymptotically Distribution-free Methods; 3.6 Some Iterative Procedures; Appendix 3.1: Matrix Calculus; Appendix 3.2: Some Basic Results in Probability Theory; Appendix 3.3: Proofs of Some Results; References; 4 Bayesian Estimation of Structural Equation Models; 4.1 Introduction; 4.2 Basic Principles and Concepts of Bayesian Analysis of SEMs; 4.3 Bayesian Estimation of the CFA Model; 4.4 Bayesian Estimation of Standard SEMs; 4.5 Bayesian Estimation via WinBUGS; Appendix 4.1: The Metropolis-Hastings Algorithm 6.3 Bayesian Estimation and Goodness-of-fit6.4 Bayesian Model Comparison; 6.5 Application 1: Bayesian Selection of the Number of Factors in EFA; 6.6 Application 2: Bayesian Analysis of Quality of Life Data; References; 7 Structural Equation Models with Dichotomous Variables; 7.1 Introduction; 7.2 Bayesian Analysis; 7.3 Analysis of a Multivariate Probit Confirmatory Factor Analysis Model; 7.4 Discussion; Appendix 7.1: Questions Associated with the Manifest Variables; References; 8 Nonlinear Structural Equation Models; 8.1 Introduction; 8.2 Bayesian Analysis of a Nonlinear SEM 8.3 Bayesian Estimation of Nonlinear SEMs with Mixed Continuous and Ordered Categorical Variables8.4 Bayesian Estimation of SEMs with Nonlinear Covariates and Latent Variables; 8.5 Bayesian Model Comparison; References; 9 Two-level Nonlinear Structural Equation Models; 9.1 Introduction; 9.2 A Two-level Nonlinear SEM with Mixed Type Variables; 9.3 Bayesian Estimation; 9.4 Goodness-of-fit and Model Comparison; 9.5 An Application: Filipina CSWs Study; 9.6 Two-level Nonlinear SEMs with Cross-level Effects; 9.7 Analysis of Two-level Nonlinear SEMs using WinBUGS Appendix 9.1: Conditional Distributions: Two-level Nonlinear SEM |
| Record Nr. | UNINA-9910829836903321 |
|
Lee Sik-Yum
|
||
| Chichester, England ; ; Hoboken, NJ, : Wiley, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Structural equation modeling [[electronic resource] ] : a Bayesian approach / / Sik-Yum Lee
| Structural equation modeling [[electronic resource] ] : a Bayesian approach / / Sik-Yum Lee |
| Autore | Lee Sik-Yum |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : Wiley, c2007 |
| Descrizione fisica | 1 online resource (459 p.) |
| Disciplina |
519.53
519.535 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Structural equation modeling
Bayesian statistical decision theory |
| ISBN |
1-280-83855-8
9786610838554 0-470-02473-9 0-470-02424-0 |
| Classificazione | 31.73 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Structural Equation Modeling; Contents; About the Author; Preface; 1 Introduction; 1.1 Standard Structural Equation Models; 1.2 Covariance Structure Analysis; 1.3 Why a New Book?; 1.4 Objectives of the Book; 1.5 Data Sets and Notations; Appendix 1.1; References; 2 Some Basic Structural Equation Models; 2.1 Introduction; 2.2 Exploratory Factor Analysis; 2.3 Confirmatory and Higher-order Factor Analysis Models; 2.4 The LISREL Model; 2.5 The Bentler-Weeks Model; 2.6 Discussion; References; 3 Covariance Structure Analysis; 3.1 Introduction; 3.2 Definitions, Notations and Preliminary Results
3.3 GLS Analysis of Covariance Structure3.4 ML Analysis of Covariance Structure; 3.5 Asymptotically Distribution-free Methods; 3.6 Some Iterative Procedures; Appendix 3.1: Matrix Calculus; Appendix 3.2: Some Basic Results in Probability Theory; Appendix 3.3: Proofs of Some Results; References; 4 Bayesian Estimation of Structural Equation Models; 4.1 Introduction; 4.2 Basic Principles and Concepts of Bayesian Analysis of SEMs; 4.3 Bayesian Estimation of the CFA Model; 4.4 Bayesian Estimation of Standard SEMs; 4.5 Bayesian Estimation via WinBUGS; Appendix 4.1: The Metropolis-Hastings Algorithm 6.3 Bayesian Estimation and Goodness-of-fit6.4 Bayesian Model Comparison; 6.5 Application 1: Bayesian Selection of the Number of Factors in EFA; 6.6 Application 2: Bayesian Analysis of Quality of Life Data; References; 7 Structural Equation Models with Dichotomous Variables; 7.1 Introduction; 7.2 Bayesian Analysis; 7.3 Analysis of a Multivariate Probit Confirmatory Factor Analysis Model; 7.4 Discussion; Appendix 7.1: Questions Associated with the Manifest Variables; References; 8 Nonlinear Structural Equation Models; 8.1 Introduction; 8.2 Bayesian Analysis of a Nonlinear SEM 8.3 Bayesian Estimation of Nonlinear SEMs with Mixed Continuous and Ordered Categorical Variables8.4 Bayesian Estimation of SEMs with Nonlinear Covariates and Latent Variables; 8.5 Bayesian Model Comparison; References; 9 Two-level Nonlinear Structural Equation Models; 9.1 Introduction; 9.2 A Two-level Nonlinear SEM with Mixed Type Variables; 9.3 Bayesian Estimation; 9.4 Goodness-of-fit and Model Comparison; 9.5 An Application: Filipina CSWs Study; 9.6 Two-level Nonlinear SEMs with Cross-level Effects; 9.7 Analysis of Two-level Nonlinear SEMs using WinBUGS Appendix 9.1: Conditional Distributions: Two-level Nonlinear SEM |
| Record Nr. | UNINA-9910841405503321 |
|
Lee Sik-Yum
|
||
| Chichester, England ; ; Hoboken, NJ, : Wiley, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||