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Applied latent class analysis / / edited by Jacques A. Hagenaars, Allan L. McCutcheon [[electronic resource]]
| Applied latent class analysis / / edited by Jacques A. Hagenaars, Allan L. McCutcheon [[electronic resource]] |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2002 |
| Descrizione fisica | 1 online resource (xxii, 454 pages) : digital, PDF file(s) |
| Disciplina | 519.5/35 |
| Soggetto topico |
Latent structure analysis
Latent variables |
| ISBN |
1-107-12755-6
1-280-41726-9 9786610417261 1-139-14563-0 0-511-18067-5 0-511-06594-9 0-511-05963-9 0-511-32640-8 0-511-49953-1 0-511-06807-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface / Jacques A. Hagenaars and Allan L. McCutcheon -- 1. Latent Class Analysis: The Empirical Study of Latent Types, Latent Variables, and Latent Structures / Leo A. Goodman -- 2. Basic Concepts and Procedures in Single- and Multiple-Group Latent Class Analysis / Allan L. McCutcheon -- 3. Latent Class Cluster Analysis / Jeroen K. Vermunt and Jay Magidson -- 4. Some Examples of Latent Budget Analysis and Its Extensions / Peter G.M. van der Heijden, L. Andries van der Ark and Ab Mooijaart -- 5. Ordering the Classes / Marcel Croon -- 6. Comparison and Choice: Analyzing Discrete Preference Data by Latent Class Scaling Models / Ulf Bockenholt -- 7. Three-Parameter Linear Logistic Latent Class Analysis / Anton K. Formann and Thomas Kohlmann -- 8. Use of Categorical and Continuous Covariates in Latent Class Analysis / C. Mitchell Dayton and George B. Macready -- 9. Directed Loglinear Modeling with Latent Variables: Causal Models for Categorical Data with Nonsystematic and Systematic Measurement Errors / Jacques A. Hagenaars -- 10. Latent Class Models for Longitudinal Data / Linda M. Collins and Brian P. Flaherty -- 11. Latent Markov Chains / Rolf Langeheine and Frank van de Pol -- 12. A Latent Class Approach to Measuring the Fit of a Statistical Model / Tamas Rudas -- 13. Mixture Regression Models / Michel Wedel and Wayne S. DeSarbo -- 14. A General Latent Class Approach to Unobserved Heterogeneity in the Analysis of Event History Data / Jeroen K. Vermunt -- 15. Latent Class Models for Contingency Tables with Missing Data / Christopher Winship, Robert D. Mare and John Robert Warren. |
| Record Nr. | UNINA-9910450089003321 |
| Cambridge : , : Cambridge University Press, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied latent class analysis / / edited by Jacques A. Hagenaars, Allan L. McCutcheon [[electronic resource]]
| Applied latent class analysis / / edited by Jacques A. Hagenaars, Allan L. McCutcheon [[electronic resource]] |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2002 |
| Descrizione fisica | 1 online resource (xxii, 454 pages) : digital, PDF file(s) |
| Disciplina | 519.5/35 |
| Soggetto topico |
Latent structure analysis
Latent variables |
| ISBN |
1-107-12755-6
1-280-41726-9 9786610417261 1-139-14563-0 0-511-18067-5 0-511-06594-9 0-511-05963-9 0-511-32640-8 0-511-49953-1 0-511-06807-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface / Jacques A. Hagenaars and Allan L. McCutcheon -- 1. Latent Class Analysis: The Empirical Study of Latent Types, Latent Variables, and Latent Structures / Leo A. Goodman -- 2. Basic Concepts and Procedures in Single- and Multiple-Group Latent Class Analysis / Allan L. McCutcheon -- 3. Latent Class Cluster Analysis / Jeroen K. Vermunt and Jay Magidson -- 4. Some Examples of Latent Budget Analysis and Its Extensions / Peter G.M. van der Heijden, L. Andries van der Ark and Ab Mooijaart -- 5. Ordering the Classes / Marcel Croon -- 6. Comparison and Choice: Analyzing Discrete Preference Data by Latent Class Scaling Models / Ulf Bockenholt -- 7. Three-Parameter Linear Logistic Latent Class Analysis / Anton K. Formann and Thomas Kohlmann -- 8. Use of Categorical and Continuous Covariates in Latent Class Analysis / C. Mitchell Dayton and George B. Macready -- 9. Directed Loglinear Modeling with Latent Variables: Causal Models for Categorical Data with Nonsystematic and Systematic Measurement Errors / Jacques A. Hagenaars -- 10. Latent Class Models for Longitudinal Data / Linda M. Collins and Brian P. Flaherty -- 11. Latent Markov Chains / Rolf Langeheine and Frank van de Pol -- 12. A Latent Class Approach to Measuring the Fit of a Statistical Model / Tamas Rudas -- 13. Mixture Regression Models / Michel Wedel and Wayne S. DeSarbo -- 14. A General Latent Class Approach to Unobserved Heterogeneity in the Analysis of Event History Data / Jeroen K. Vermunt -- 15. Latent Class Models for Contingency Tables with Missing Data / Christopher Winship, Robert D. Mare and John Robert Warren. |
| Record Nr. | UNINA-9910783312803321 |
| Cambridge : , : Cambridge University Press, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Current topics in the theory and application of latent variable models / / edited by Michael C. Edwards and Robert C. MacCallum
| Current topics in the theory and application of latent variable models / / edited by Michael C. Edwards and Robert C. MacCallum |
| Pubbl/distr/stampa | New York : , : Routledge, , 2013 |
| Descrizione fisica | 1 online resource (297 p.) |
| Disciplina | 519.5/35 |
| Altri autori (Persone) |
EdwardsMichael C <1977-> (Michael Charles)
MacCallumRobert C |
| Soggetto topico |
Latent structure analysis
Latent variables |
| Soggetto genere / forma | Electronic books. |
| ISBN |
0-203-81340-5
1-283-89358-4 1-136-69980-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. Complexities in latent variable modeling -- pt. 2. Drawing meaning from latent variable models. |
| Record Nr. | UNINA-9910452978103321 |
| New York : , : Routledge, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Current topics in the theory and application of latent variable models / / edited by Michael C. Edwards and Robert C. MacCallum
| Current topics in the theory and application of latent variable models / / edited by Michael C. Edwards and Robert C. MacCallum |
| Pubbl/distr/stampa | New York : , : Routledge, , 2013 |
| Descrizione fisica | 1 online resource (297 p.) |
| Disciplina | 519.5/35 |
| Altri autori (Persone) |
EdwardsMichael C <1977-> (Michael Charles)
MacCallumRobert C |
| Soggetto topico |
Latent structure analysis
Latent variables |
| ISBN |
1-136-69979-1
0-203-81340-5 1-283-89358-4 1-136-69980-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. Complexities in latent variable modeling -- pt. 2. Drawing meaning from latent variable models. |
| Record Nr. | UNINA-9910779306503321 |
| New York : , : Routledge, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Current topics in the theory and application of latent variable models / / edited by Michael C. Edwards and Robert C. MacCallum
| Current topics in the theory and application of latent variable models / / edited by Michael C. Edwards and Robert C. MacCallum |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York : , : Routledge, , 2013 |
| Descrizione fisica | 1 online resource (297 p.) |
| Disciplina | 519.5/35 |
| Altri autori (Persone) |
EdwardsMichael C <1977-> (Michael Charles)
MacCallumRobert C |
| Soggetto topico |
Latent structure analysis
Latent variables |
| ISBN |
1-136-69979-1
0-203-81340-5 1-283-89358-4 1-136-69980-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. Complexities in latent variable modeling -- pt. 2. Drawing meaning from latent variable models. |
| Record Nr. | UNINA-9910964916603321 |
| New York : , : Routledge, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Latent class and latent transition analysis : with applications in the social, behavioral, and health sciences / / Linda M. Collins, Stephanie T. Lanza
| Latent class and latent transition analysis : with applications in the social, behavioral, and health sciences / / Linda M. Collins, Stephanie T. Lanza |
| Autore | Collins Linda M |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2010 |
| Descrizione fisica | 1 online resource (331 p.) |
| Disciplina |
300.15195
519.535 |
| Altri autori (Persone) | LanzaStephanie T. <1969-> |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Latent structure analysis
Latent variables Statistics |
| ISBN |
9786612687150
9781118210765 111821076X 9781282687158 1282687158 9780470567333 0470567333 9780470567326 0470567325 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences; CONTENTS; List of Figures; List of Tables; Acknowledgments; Acronyms; PART I FUNDAMENTALS; 1 General Introduction; 1.1 Overview; 1.2 Conceptual foundation and brief history of the latent class model; 1.2.1 LCA and other latent variable models; 1.2.2 Some historical milestones in LCA; 1.2.3 LCA as a person-oriented approach; 1.3 Why select a categorical latent variable approach?; 1.4 Scope of this book; 1.5 Empirical example of LCA: Adolescent delinquency
1.6 Empirical example of LTA: Adolescent delinquency1.7 About this book; 1.7.1 Using this book; 1.8 The examples in this book; 1.8.1 Empirical data sets; 1.9 Software; 1.10 Additional resources: The book's web site; 1.11 Suggested supplemental readings; 1.12 Points to remember; 1.13 What's next; 2 The latent class model; 2.1 Overview; 2.2 Empirical example: Pubertal development; 2.2.1 An initial look at the data; 2.2.2 Why conduct LCA on the pubertal development data?; 2.2.3 Latent classes in the pubertal development data 2.3 The role of item-response probabilities in interpreting latent classes2.3.1 A hypothetical example; 2.3.2 Interpreting the item-response probabilities to label the latent classes in the pubertal development example; 2.3.3 Qualitative and quantitative differences among the pubertal development latent classes; 2.4 Empirical example: Health risk behaviors; 2.4.1 An initial look at the data; 2.4.2 LCA of the health risk behavior data; 2.5 LCA: Model and notation; 2.5.1 Fundamental expressions; 2.5.2 The local independence assumption; 2.6 Suggested supplemental readings; 2.7 Points to remember 2.8 What's next3 The relation between the latent variable and its indicators; 3.1 Overview; 3.2 The latent class measurement model; 3.2.1 Parallels with factor analysis; 3.2.2 Two criteria for evaluating item-response probabilities for a single variable; 3.2.3 Hypothetical and empirical examples of independence and weak relations; 3.2.4 Hypothetical and empirical examples of strong relations; 3.3 Homogeneity and latent class separation; 3.3.1 Homogeneity; 3.3.2 Latent class separation; 3.3.3 Hypothetical examples of homogeneity and latent class separation 3.3.4 How homogeneity and latent class separation are related3.3.5 Homogeneity, latent class separation, and the number of response patterns observed; 3.3.6 Homogeneity and latent class separation in empirical examples; 3.4 The precision with which the observed variables measure the latent variable; 3.4.1 Why posterior probabilities of latent class membership are of interest; 3.4.2 Bayes' theorem; 3.4.3 What homogeneity and latent class separation imply about posterior probabilities and classification uncertainty 3.4.4 Posterior classification uncertainty even with a high degree of homogeneity and latent class separation |
| Record Nr. | UNINA-9910139489803321 |
Collins Linda M
|
||
| Hoboken, NJ, : Wiley, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Latent curve models [[electronic resource] ] : a structural equation perspective / / Kenneth A. Bollen, Patrick J. Curran
| Latent curve models [[electronic resource] ] : a structural equation perspective / / Kenneth A. Bollen, Patrick J. Curran |
| Autore | Bollen Kenneth A |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (307 p.) |
| Disciplina |
519.5/35
621.384135015118 |
| Altri autori (Persone) | CurranPatrick J. <1965-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Latent structure analysis
Latent variables |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-40940-1
9786610409402 0-470-32167-9 0-471-74609-6 0-471-74608-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Latent Curve Models; Contents; Preface; 1 Introduction; 1.1 Conceptualization and Analysis of Trajectories; 1.1.1 Trajectories of Crime Rates; 1.1.2 Data Requirements; 1.1.3 Summary; 1.2 Three Initial Questions About Trajectories; 1.2.1 Question 1: What Is the Trajectory for the Entire Group?; 1.2.2 Question 2: Do We Need Distinct Trajectories for Each Case?; 1.2.3 Question 3: If Distinct Trajectories Are Needed, Can We Identify Variables to Predict These Individual Trajectories?; 1.2.4 Summary; 1.3 Brief History of Latent Curve Models; 1.3.1 Early Developments: The Nineteenth Century
1.3.2 Fitting Group Trajectories: 1900-19371.3.3 Fitting Individual and Group Trajectories: 1938-1950s; 1.3.4 Trajectory Modeling with Latent Variables: 1950s-1984; 1.3.5 Current Latent Curve Modeling: 1984-present; 1.3.6 Summary; 1.4 Organization of the Remainder of the Book; 2 Unconditional Latent Curve Model; 2.1 Repeated Measures; 2.2 General Model and Assumptions; 2.3 Identification; 2.4 Case-By-Case Approach; 2.4.1 Assessing Model Fit; 2.4.2 Limitations of Case-by-Case Approach; 2.5 Structural Equation Model Approach; 2.5.1 Matrix Expression of the Latent Curve Model 2.5.2 Maximum Likelihood Estimation2.5.3 Empirical Example; 2.5.4 Assessing Model Fit; 2.5.5 Components of Fit; 2.6 Alternative Approaches to the SEM; 2.7 Conclusions; Appendix 2A: Test Statistics, Nonnormality, and Statistical Power; 3 Missing Data and Alternative Metrics of Time; 3.1 Missing Data; 3.1.1 Types of Missing Data; 3.1.2 Treatment of Missing Data; 3.1.3 Empirical Example; 3.1.4 Summary; 3.2 Missing Data and Alternative Metrics of Time; 3.2.1 Numerical Measure of Time; 3.2.2 When Wave of Assessment and Alternative Metrics of Time Are Equivalent 3.2.3 When Wave of Assessment and Alternative Metrics of Time Are Different3.2.4 Reorganizing Data as a Function of Alternative Metrics of Time; 3.2.5 Individually Varying Values of Time; 3.2.6 Summary; 3.2.7 Empirical Example: Reading Achievement; 3.3 Conclusions; 4 Nonlinear Trajectories and the Coding of Time; 4.1 Modeling Nonlinear Functions of Time; 4.1.1 Polynomial Trajectories: Quadratic Trajectory Model; 4.1.2 Polynomial Trajectories: Cubic Trajectory Models; 4.1.3 Summary; 4.2 Nonlinear Curve Fitting: Estimated Factor Loadings; 4.2.1 Selecting the Metric of Change 4.3 Piecewise Linear Trajectory Models4.3.1 Identification; 4.3.2 Interpretation; 4.4 Alternative Parametric Functions; 4.4.1 Exponential Trajectory; 4.4.2 Parametric Functions with Cycles; 4.4.3 Nonlinear Transformations of the Metric of Time; 4.4.4 Nonlinear Transformations of the Repeated Measures; 4.5 Linear Transformations of the Metric of Time; 4.5.1 Logic of Recoding the Metric of Time; 4.5.2 General Framework for Transforming Time; 4.5.3 Summary; 4.6 Conclusions; Appendix 4A: Identification of Quadratic and Piecewise Latent Curve Models; 4A.1 Quadratic LCM; 4A.2 Piecewise LCM 5 Conditional Latent Curve Models |
| Record Nr. | UNINA-9910143577103321 |
|
Bollen Kenneth A
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Latent curve models [[electronic resource] ] : a structural equation perspective / / Kenneth A. Bollen, Patrick J. Curran
| Latent curve models [[electronic resource] ] : a structural equation perspective / / Kenneth A. Bollen, Patrick J. Curran |
| Autore | Bollen Kenneth A |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (307 p.) |
| Disciplina |
519.5/35
621.384135015118 |
| Altri autori (Persone) | CurranPatrick J. <1965-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Latent structure analysis
Latent variables |
| ISBN |
1-280-40940-1
9786610409402 0-470-32167-9 0-471-74609-6 0-471-74608-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Latent Curve Models; Contents; Preface; 1 Introduction; 1.1 Conceptualization and Analysis of Trajectories; 1.1.1 Trajectories of Crime Rates; 1.1.2 Data Requirements; 1.1.3 Summary; 1.2 Three Initial Questions About Trajectories; 1.2.1 Question 1: What Is the Trajectory for the Entire Group?; 1.2.2 Question 2: Do We Need Distinct Trajectories for Each Case?; 1.2.3 Question 3: If Distinct Trajectories Are Needed, Can We Identify Variables to Predict These Individual Trajectories?; 1.2.4 Summary; 1.3 Brief History of Latent Curve Models; 1.3.1 Early Developments: The Nineteenth Century
1.3.2 Fitting Group Trajectories: 1900-19371.3.3 Fitting Individual and Group Trajectories: 1938-1950s; 1.3.4 Trajectory Modeling with Latent Variables: 1950s-1984; 1.3.5 Current Latent Curve Modeling: 1984-present; 1.3.6 Summary; 1.4 Organization of the Remainder of the Book; 2 Unconditional Latent Curve Model; 2.1 Repeated Measures; 2.2 General Model and Assumptions; 2.3 Identification; 2.4 Case-By-Case Approach; 2.4.1 Assessing Model Fit; 2.4.2 Limitations of Case-by-Case Approach; 2.5 Structural Equation Model Approach; 2.5.1 Matrix Expression of the Latent Curve Model 2.5.2 Maximum Likelihood Estimation2.5.3 Empirical Example; 2.5.4 Assessing Model Fit; 2.5.5 Components of Fit; 2.6 Alternative Approaches to the SEM; 2.7 Conclusions; Appendix 2A: Test Statistics, Nonnormality, and Statistical Power; 3 Missing Data and Alternative Metrics of Time; 3.1 Missing Data; 3.1.1 Types of Missing Data; 3.1.2 Treatment of Missing Data; 3.1.3 Empirical Example; 3.1.4 Summary; 3.2 Missing Data and Alternative Metrics of Time; 3.2.1 Numerical Measure of Time; 3.2.2 When Wave of Assessment and Alternative Metrics of Time Are Equivalent 3.2.3 When Wave of Assessment and Alternative Metrics of Time Are Different3.2.4 Reorganizing Data as a Function of Alternative Metrics of Time; 3.2.5 Individually Varying Values of Time; 3.2.6 Summary; 3.2.7 Empirical Example: Reading Achievement; 3.3 Conclusions; 4 Nonlinear Trajectories and the Coding of Time; 4.1 Modeling Nonlinear Functions of Time; 4.1.1 Polynomial Trajectories: Quadratic Trajectory Model; 4.1.2 Polynomial Trajectories: Cubic Trajectory Models; 4.1.3 Summary; 4.2 Nonlinear Curve Fitting: Estimated Factor Loadings; 4.2.1 Selecting the Metric of Change 4.3 Piecewise Linear Trajectory Models4.3.1 Identification; 4.3.2 Interpretation; 4.4 Alternative Parametric Functions; 4.4.1 Exponential Trajectory; 4.4.2 Parametric Functions with Cycles; 4.4.3 Nonlinear Transformations of the Metric of Time; 4.4.4 Nonlinear Transformations of the Repeated Measures; 4.5 Linear Transformations of the Metric of Time; 4.5.1 Logic of Recoding the Metric of Time; 4.5.2 General Framework for Transforming Time; 4.5.3 Summary; 4.6 Conclusions; Appendix 4A: Identification of Quadratic and Piecewise Latent Curve Models; 4A.1 Quadratic LCM; 4A.2 Piecewise LCM 5 Conditional Latent Curve Models |
| Record Nr. | UNINA-9910830947003321 |
|
Bollen Kenneth A
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Latent curve models : a structural equation perspective / / Kenneth A. Bollen, Patrick J. Curran
| Latent curve models : a structural equation perspective / / Kenneth A. Bollen, Patrick J. Curran |
| Autore | Bollen Kenneth A |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (307 p.) |
| Disciplina | 519.5/35 |
| Altri autori (Persone) | CurranPatrick J. <1965-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Latent structure analysis
Latent variables |
| ISBN |
1-280-40940-1
9786610409402 0-470-32167-9 0-471-74609-6 0-471-74608-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Latent Curve Models; Contents; Preface; 1 Introduction; 1.1 Conceptualization and Analysis of Trajectories; 1.1.1 Trajectories of Crime Rates; 1.1.2 Data Requirements; 1.1.3 Summary; 1.2 Three Initial Questions About Trajectories; 1.2.1 Question 1: What Is the Trajectory for the Entire Group?; 1.2.2 Question 2: Do We Need Distinct Trajectories for Each Case?; 1.2.3 Question 3: If Distinct Trajectories Are Needed, Can We Identify Variables to Predict These Individual Trajectories?; 1.2.4 Summary; 1.3 Brief History of Latent Curve Models; 1.3.1 Early Developments: The Nineteenth Century
1.3.2 Fitting Group Trajectories: 1900-19371.3.3 Fitting Individual and Group Trajectories: 1938-1950s; 1.3.4 Trajectory Modeling with Latent Variables: 1950s-1984; 1.3.5 Current Latent Curve Modeling: 1984-present; 1.3.6 Summary; 1.4 Organization of the Remainder of the Book; 2 Unconditional Latent Curve Model; 2.1 Repeated Measures; 2.2 General Model and Assumptions; 2.3 Identification; 2.4 Case-By-Case Approach; 2.4.1 Assessing Model Fit; 2.4.2 Limitations of Case-by-Case Approach; 2.5 Structural Equation Model Approach; 2.5.1 Matrix Expression of the Latent Curve Model 2.5.2 Maximum Likelihood Estimation2.5.3 Empirical Example; 2.5.4 Assessing Model Fit; 2.5.5 Components of Fit; 2.6 Alternative Approaches to the SEM; 2.7 Conclusions; Appendix 2A: Test Statistics, Nonnormality, and Statistical Power; 3 Missing Data and Alternative Metrics of Time; 3.1 Missing Data; 3.1.1 Types of Missing Data; 3.1.2 Treatment of Missing Data; 3.1.3 Empirical Example; 3.1.4 Summary; 3.2 Missing Data and Alternative Metrics of Time; 3.2.1 Numerical Measure of Time; 3.2.2 When Wave of Assessment and Alternative Metrics of Time Are Equivalent 3.2.3 When Wave of Assessment and Alternative Metrics of Time Are Different3.2.4 Reorganizing Data as a Function of Alternative Metrics of Time; 3.2.5 Individually Varying Values of Time; 3.2.6 Summary; 3.2.7 Empirical Example: Reading Achievement; 3.3 Conclusions; 4 Nonlinear Trajectories and the Coding of Time; 4.1 Modeling Nonlinear Functions of Time; 4.1.1 Polynomial Trajectories: Quadratic Trajectory Model; 4.1.2 Polynomial Trajectories: Cubic Trajectory Models; 4.1.3 Summary; 4.2 Nonlinear Curve Fitting: Estimated Factor Loadings; 4.2.1 Selecting the Metric of Change 4.3 Piecewise Linear Trajectory Models4.3.1 Identification; 4.3.2 Interpretation; 4.4 Alternative Parametric Functions; 4.4.1 Exponential Trajectory; 4.4.2 Parametric Functions with Cycles; 4.4.3 Nonlinear Transformations of the Metric of Time; 4.4.4 Nonlinear Transformations of the Repeated Measures; 4.5 Linear Transformations of the Metric of Time; 4.5.1 Logic of Recoding the Metric of Time; 4.5.2 General Framework for Transforming Time; 4.5.3 Summary; 4.6 Conclusions; Appendix 4A: Identification of Quadratic and Piecewise Latent Curve Models; 4A.1 Quadratic LCM; 4A.2 Piecewise LCM 5 Conditional Latent Curve Models |
| Record Nr. | UNINA-9911020148103321 |
|
Bollen Kenneth A
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Latent variable models and factor analysis : a unified approach / / David Bartholomew, Martin Knott, Irini Moustaki
| Latent variable models and factor analysis : a unified approach / / David Bartholomew, Martin Knott, Irini Moustaki |
| Autore | Bartholomew David J |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2011 |
| Descrizione fisica | xiii, 277 p. : ill |
| Disciplina | 519.5/35 |
| Altri autori (Persone) |
KnottM (Martin)
MoustakiIrini |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Latent variables
Latent structure analysis Factor analysis |
| ISBN |
9786613177698
9781283177696 1283177692 9781119970590 1119970598 9781119970583 111997058X 9781119973706 1119973708 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Latent Variable Models and Factor Analysis -- Contents -- Preface -- Acknowledgements -- 1 Basic ideas and examples -- 1.1 The statistical problem -- 1.2 The basic idea -- 1.3 Two examples -- 1.3.1 Binary manifest variables and a single binary latent variable -- 1.3.2 A model based on normal distributions -- 1.4 A broader theoretical view -- 1.5 Illustration of an alternative approach -- 1.6 An overview of special cases -- 1.7 Principal components -- 1.8 The historical context -- 1.9 Closely related fields in statistics -- 2 The general linear latent variable model -- 2.1 Introduction -- 2.2 The model -- 2.3 Some properties of the model -- 2.4 A special case -- 2.5 The sufficiency principle -- 2.6 Principal special cases -- 2.7 Latent variable models with non-linear terms -- 2.8 Fitting the models -- 2.9 Fitting by maximum likelihood -- 2.10 Fitting by Bayesian methods -- 2.11 Rotation -- 2.12 Interpretation -- 2.13 Sampling error of parameter estimates -- 2.14 The prior distribution -- 2.15 Posterior analysis -- 2.16 A further note on the prior -- 2.17 Psychometric inference -- 3 The normal linear factor model -- 3.1 The model -- 3.2 Some distributional properties -- 3.3 Constraints on the model -- 3.4 Maximum likelihood estimation -- 3.5 Maximum likelihood estimation by the E-M algorithm -- 3.6 Sampling variation of estimators -- 3.7 Goodness of fit and choice of q -- 3.7.1 Model selection criteria -- 3.8 Fitting without normality assumptions: least squares methods -- 3.9 Other methods of fitting -- 3.10 Approximate methods for estimating -- 3.11 Goodness of fit and choice of q for least squares methods -- 3.12 Further estimation issues -- 3.12.1 Consistency -- 3.12.2 Scale-invariant estimation -- 3.12.3 Heywood cases -- 3.13 Rotation and related matters -- 3.13.1 Orthogonal rotation -- 3.13.2 Oblique rotation -- 3.13.3 Related matters.
3.14 Posterior analysis: the normal case -- 3.15 Posterior analysis: least squares -- 3.16 Posterior analysis: a reliability approach -- 3.17 Examples -- 4 Binary data: latent trait models -- 4.1 Preliminaries -- 4.2 The logit/normal model -- 4.3 The probit/normal model -- 4.4 The equivalence of the response function and underlying variable approaches -- 4.5 Fitting the logit/normal model: the E-M algorithm -- 4.5.1 Fitting the probit/normal model -- 4.5.2 Other methods for approximating the integral -- 4.6 Sampling properties of the maximum likelihood estimators -- 4.7 Approximate maximum likelihood estimators -- 4.8 Generalised least squares methods -- 4.9 Goodness of fit -- 4.10 Posterior analysis -- 4.11 Fitting the logit/normal and probit/normal models: Markov chain Monte Carlo -- 4.11.1 Gibbs sampling -- 4.11.2 Metropolis-Hastings -- 4.11.3 Choosing prior distributions -- 4.11.4 Convergence diagnostics in MCMC -- 4.12 Divergence of the estimation algorithm -- 4.13 Examples -- 5 Polytomous data: latent trait models -- 5.1 Introduction -- 5.2 A response function model based on the sufficiency principle -- 5.3 Parameter interpretation -- 5.4 Rotation -- 5.5 Maximum likelihood estimation of the polytomous logit model -- 5.6 An approximation to the likelihood -- 5.6.1 One factor -- 5.6.2 More than one factor -- 5.7 Binary data as a special case -- 5.8 Ordering of categories -- 5.8.1 A response function model for ordinal variables -- 5.8.2 Maximum likelihood estimation of the model with ordinal variables -- 5.8.3 The partial credit model -- 5.8.4 An underlying variable model -- 5.9 An alternative underlying variable model -- 5.10 Posterior analysis -- 5.11 Further observations -- 5.12 Examples of the analysis of polytomous data using the logit model -- 6 Latent class models -- 6.1 Introduction. 6.2 The latent class model with binary manifest variables -- 6.3 The latent class model for binary data as a latent trait model -- 6.4 K latent classes within the GLLVM -- 6.5 Maximum likelihood estimation -- 6.6 Standard errors -- 6.7 Posterior analysis of the latent class model with binary manifest variables -- 6.8 Goodness of fit -- 6.9 Examples for binary data -- 6.10 Latent class models with unordered polytomous manifest variables -- 6.11 Latent class models with ordered polytomous manifest variables -- 6.12 Maximum likelihood estimation -- 6.12.1 Allocation of individuals to latent classes -- 6.13 Examples for unordered polytomous data -- 6.14 Identifiability -- 6.15 Starting values -- 6.16 Latent class models with metrical manifest variables -- 6.16.1 Maximum likelihood estimation -- 6.16.2 Other methods -- 6.16.3 Allocation to categories -- 6.17 Models with ordered latent classes -- 6.18 Hybrid models -- 6.18.1 Hybrid model with binary manifest variables -- 6.18.2 Maximum likelihood estimation -- 7 Models and methods for manifest variables of mixed type -- 7.1 Introduction -- 7.2 Principal results -- 7.3 Other members of the exponential family -- 7.3.1 The binomial distribution -- 7.3.2 The Poisson distribution -- 7.3.3 The gamma distribution -- 7.4 Maximum likelihood estimation -- 7.4.1 Bernoulli manifest variables -- 7.4.2 Normal manifest variables -- 7.4.3 A general E-M approach to solving the likelihood equations -- 7.4.4 Interpretation of latent variables -- 7.5 Sampling properties and goodness of fit -- 7.6 Mixed latent class models -- 7.7 Posterior analysis -- 7.8 Examples -- 7.9 Ordered categorical variables and other generalisations -- 8 Relationships between latent variables -- 8.1 Scope -- 8.2 Correlated latent variables -- 8.3 Procrustes methods -- 8.4 Sources of prior knowledge -- 8.5 Linear structural relations models. 8.6 The LISREL model -- 8.6.1 The structural model -- 8.6.2 The measurement model -- 8.6.3 The model as a whole -- 8.7 Adequacy of a structural equation model -- 8.8 Structural relationships in a general setting -- 8.9 Generalisations of the LISREL model -- 8.10 Examples of models which are indistinguishable -- 8.11 Implications for analysis -- 9 Related techniques for investigating dependency -- 9.1 Introduction -- 9.2 Principal components analysis -- 9.2.1 A distributional treatment -- 9.2.2 A sample-based treatment -- 9.2.3 Unordered categorical data -- 9.2.4 Ordered categorical data -- 9.3 An alternative to the normal factor model -- 9.4 Replacing latent variables by linear functions of the manifest variables -- 9.5 Estimation of correlations and regressions between latent variables -- 9.6 Q-Methodology -- 9.7 Concluding reflections of the role of latent variables in statistical modelling -- Software appendix -- References -- Author index -- Subject index. |
| Record Nr. | UNINA-9910208838003321 |
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Bartholomew David J
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| Hoboken, N.J., : Wiley, 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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