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  • 1
    Online Resource
    Online Resource
    Recent Developments on Structural Equation Models : Theory and Applications (2004)
    Dordrecht : Springer Netherlands
    Details
    UID:
    b3kat_BV042419232
    Format: 1 Online-Ressource (XVI, 358 p)
    ISBN: 9781402019586 , 9789048165490
    Series Statement: Mathematical Modelling: Theory and Applications 19
    Note: After Karl Jöreskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and statisticians professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of Structural Equation Modeling in solving their problems. Finally, methodologists, mathematicians and applied researchers alike are addressed, who simply want to update their knowledge of recent approaches in data analysis and mathematical modelling
    Language: English
    Keywords: Multivariate Analyse ; Sozialwissenschaften ; Statistik
    DOI: 10.1007/978-1-4020-1958-6
    URL: Volltext
    URL: Volltext  (lizenzpflichtig)
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  • 2
    Online Resource
    Online Resource
    Innovations in Multivariate Statistical Analysis : A Festschrift for Heinz Neudecker (2000)
    New York, NY :Springer US :
    Details
    UID:
    almahu_9949285164802882
    Format: XIII, 298 p. , online resource.
    Edition: 1st ed. 2000.
    ISBN: 9781461546030
    Series Statement: Advanced Studies in Theoretical and Applied Econometrics, 36
    Content: The three decades which have followed the publication of Heinz Neudecker's seminal paper `Some Theorems on Matrix Differentiation with Special Reference to Kronecker Products' in the Journal of the American Statistical Association (1969) have witnessed the growing influence of matrix analysis in many scientific disciplines. Amongst these are the disciplines to which Neudecker has contributed directly - namely econometrics, economics, psychometrics and multivariate analysis. This book aims to illustrate how powerful the tools of matrix analysis have become as weapons in the statistician's armoury. The majority of its chapters are concerned primarily with theoretical innovations, but all of them have applications in view, and some of them contain extensive illustrations of the applied techniques. This book will provide research workers and graduate students with a cross-section of innovative work in the fields of matrix methods and multivariate statistical analysis. It should be of interest to students and practitioners in a wide range of subjects which rely upon modern methods of statistical analysis. The contributors to the book are themselves practitioners of a wide range of subjects including econometrics, psychometrics, educational statistics, computation methods and electrical engineering, but they find a common ground in the methods which are represented in the book. It is envisaged that the book will serve as an important work of reference and as a source of inspiration for some years to come.
    Note: 1 Some Comments and a Bibliography on the Frucht-Kantorovich and Wielandt Inequalities -- 1.1 Introduction and Mise-en-scène: The Frucht-Kantorovich Inequality -- 1.2 The Wielandt Inequality -- 1.3 The Schweitzer Inequality -- 1.4 The Pólya-Szegö Inequality -- 1.5 The Cassels, Krasnosel'ski?-Kre?n and Greub-Rheinboldt Inequalities -- 1.6 The Bloomfield-Watson-Knott Inequality -- 1.7 Some Other Related Inequalities -- 2 On Matrix Trace Kantorovich-type Inequalities -- 2.1 Introduction -- 2.2 Basic Inequalities -- 2.3 Mathematical Results -- 2.4 Statistical Applications -- 3 Matrix Inequality Applications in Econometrics -- 3.1 Introduction -- 3.2 Equivalent Covariance Matrices in the Multinomial Probit Model -- 3.3 Matrix Inequalities in Regression Analysis -- 3.4 A Condition for the Positivity of the MINQUE -- 3.5 Eigenvalues and Eigenvectors of a Bounded Matrix -- 3.6 Proxies and Measurement Error -- 3.7 Conclusion -- 4 On a Generalisation of the Covariance Matrix of the Multinomial Distribution -- 4.1 Introduction -- 4.2 Moore-Penrose Inverse -- 4.3 Eigenvalues -- 5 A General Method of Testing for Random Parameter Variation in Statistical Models -- 5.1 Introduction -- 5.2 Derivation of the Test -- 5.3 Examples of the Test Procedure -- 5.4 Summary -- 6 Dual Scaling and Correspondence Analysis of Rank Order Data -- 6.1 Introduction -- 6.2 Correspondence Analysis and Dual Scaling -- 6.3 Rank Order Data -- 6.4 Dual Scaling of Rank Order Data -- 6.5 Correspondence Analysis of Rank Order Data -- 6.6 Concluding Remarks -- 7 Continuous Extensions of Matrix Formulations in Correspondence Analysis, with Applications to the FGM Family of Distributions -- 7.1 Introduction -- 7.2 Discrete Correspondence Analysis -- 7.3 The Chi-square Distance -- 7.4 Continuous Random Variable Extension -- 7.5 Continuous Weighted Metric Scaling -- 7.6 Geometric Variability, Proximity Function and Isometries -- 7.7 The FGM Family of Distributions and Correspondence Analysis -- 7.8 A Generalised FGM Family -- 8 Utility Maximisation and Mode of Payment -- 8.1 Introduction -- 8.2 Compatibility of Choice Probabilities with Stochastic Utility Max imisation -- 8.3 Choice of Mode of Payment -- 8.4 Compatibility with Utility Maximisation -- 8.5 Semiparametric Estimation of the Choice Model -- 8.6 Conclusion -- 9 Gibbs Sampling in B-VAR Models with Latent Variables -- 9.1 Introduction -- 9.2 The AR(p) Model with Latent Variables -- 9.3 The Multiple ARX(p) Model with Latent Variables -- 9.4 Further topics -- 9.5 Conclusions -- 10 Least-Squares Autoregression with Near-unit Root -- 10.1 Introduction -- 10.2 Regression without Intercept -- 10.3 Regression with Intercept -- 10.4 Negative Unit Root -- 10.5 Conclusions -- 11 Efficiency Comparisons for a System GMM Estimator in Dynamic Panel Data Models -- 11.1 Introduction -- 11.2 Model and System GMM Estimator -- 11.3 Efficiency Comparisons -- 11.4 Discussion -- 12 The Rank Condition for Forward Looking Models -- 12.1 Introduction -- 12.2 The Rank Condition -- 12.3 Hysteresis -- 12.4 Concluding Remarks -- 13 Notes on the Elementary Properties of Permutation and Re-flection Matrices -- 13.1 Introduction -- 13.2 Definitions -- 13.3 Basic Results -- 13.4 Samuelson Transformation Matrices -- 13.5 Samuelson Reflection Matrices -- 13.6 Givens Rotation Matrices -- 13.7 Eigenvalues of Permutation Matrices -- 13.8 Examples of Permutation Matrices -- 13.9 Concluding Remarks -- 14 S-Ancillarity and Strong Exogeneity -- 14.1 Introduction -- 14.2 The Main Result -- 14.3 An Example -- 15 Asymptotic Inference Based on Eigenprojections of Covariance and Correlation Matrices -- 15.1 Introduction -- 15.2 Preliminaries -- 15.3 Asymptotic Distribution of Eigenprojections -- 15.4 Testing H0 by the Chi-Square Test -- 16 On a Fisher-Cornish Type Expansion of Wishart Matrices -- 16.1 Introduction -- 16.2 The Symmetric Multivariate Normal Distribution -- 16.3 Asymptotic Approximations for Wishart Matrices -- 17 Scaled and Adjusted Restricted Tests in Multi-Sample Analysis of Moment Structures -- 17.1 Introduction -- 17.2 Goodness-of-fit tests -- 17.3 Restricted tests -- 17.4 Illustration -- 18 Asymptotic Behaviour of Sums of Powers of Residuals in the Classic Linear Regression Model -- 18.1 Introduction -- 18.2 Set-up and Main Results -- 19 Matrix Methods for Solving Nonlinear Dynamic Optimisation Models -- 19.1 Introduction -- 19.2 A Nonlinear Optimisation Framework -- 19.3 An Example -- 19.4 Summary -- 20 Computers, Multilinear Algebra and Statistics -- 20.1 Introduction -- 20.2 Problems with the Computer Screen -- 20.3 An Index Notation for the Computer Screen -- 20.4 The Index Notation Applied to Matrix Differential Calculus -- 20.5 Chain Rules -- Author Index.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9780792386360
    Additional Edition: Printed edition: ISBN 9781461370802
    Additional Edition: Printed edition: ISBN 9781461546047
    Language: English
    Keywords: Festschrift
    DOI: 10.1007/978-1-4615-4603-0
    URL: https://doi.org/10.1007/978-1-4615-4603-0
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 3
    Online Resource
    Online Resource
    Longitudinal Research with Latent Variables (2010)
    Berlin, Heidelberg : Springer Berlin Heidelberg
    Details
    UID:
    gbv_1649987900
    Format: Online-Ressource (XI, 301p. 42 illus, digital)
    ISBN: 9783642117602 , 9786612928000 , 9781282928008
    Series Statement: SpringerLink
    Content: Loglinear Latent Variable Models for Longitudinal Categorical Data -- Random Effects Models for Longitudinal Data -- Multivariate and Multilevel Longitudinal Analysis -- Longitudinal Research Using Mixture Models -- An Overview of the Autoregressive Latent Trajectory (ALT) Model -- State Space Methods for Latent Trajectory and Parameter Estimation by Maximum Likelihood -- Continuous Time Modeling of Panel Data by means of SEM -- Five Steps in Latent Curve and Latent Change Score Modeling with Longitudinal Data -- Structural Interdependence and Unobserved Heterogeneity in Event History Analysis.
    Content: This book combines longitudinal research and latent variable research, i.e. it explains how longitudinal studies with objectives formulated in terms of latent variables should be carried out, with an emphasis on detailing how the methods are applied. Because longitudinal research with latent variables currently utilizes different approaches with different histories, different types of research questions, and different computer programs to perform the analysis, the book is divided into nine chapters. Starting from (a) some background information about the specific approach (a short history and the main publications), each chapter then (b) describes the type of research questions the approach is able to answer, (c) provides statistical and mathematical explanations of the models used in the data analysis, (d) discusses the input and output of the programs used, and (e) provides one or more examples with typical data sets, allowing the readers to apply the programs themselves.
    Note: Includes bibliographical references , Longitudinal Research with Latent Variables; Preface; Contents; List of Contributors; 1 Loglinear Latent Variable Models for Longitudinal Categorical Data; 2 Random Effects Models for Longitudinal Data; 3 Multivariate and Multilevel Longitudinal Analysis; 4 Longitudinal Research Using Mixture Models; 5 An Overview of the Autoregressive Latent Trajectory (ALT) Model; 6 State Space Methods for Latent Trajectory and Parameter Estimation by Maximum Likelihood; 7 Continuous Time Modeling of Panel Data by means of SEM , 8 Five Steps in Latent Curve and Latent Change Score Modeling with Longitudinal Data9 Structural Interdependence and Unobserved Heterogeneity in Event History Analysis
    Additional Edition: ISBN 9783642117596
    Additional Edition: Buchausg. u.d.T. Longitudinal research with latent variables Heidelberg : Springer, 2010 ISBN 9783642117596
    Language: English
    Subjects: Mathematics
    RVK:
    SK 845
    Keywords: Längsschnittuntersuchung ; Latente Variable ; Längsschnittuntersuchung ; Latente Variable
    DOI: 10.1007/978-3-642-11760-2
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    URL: Inhaltstext
    URL: Inhaltsverzeichnis
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  • 4
    Book
    Book
    Fusion of data sets in multivariate linear regression with errors-in-variables / (1996)
    Barcelona :Universitat Pompeu Fabra,
    Show associated volumes
    Details
    UID:
    almahu_BV024991046
    Format: 14 S.
    Series Statement: Economics working papers series / Universitat Pompeu Fabra 183
    Language: English
    Subjects: Economics
    RVK:
    QB 910
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  • 5
    Online Resource
    Online Resource
    Recent Developments on Structural Equation Models : Theory and Applications (2004)
    Dordrecht :Springer Netherlands :
    Details
    UID:
    almahu_9947362731102882
    Format: XVI, 358 p. , online resource.
    ISBN: 9781402019586
    Series Statement: Mathematical Modelling: Theory and Applications, 19
    Content: After Karl Jöreskog's first presentation in 1970, Structural Equation Modelling or SEM has become a main statistical tool in many fields of science. It is the standard approach of factor analytic and causal modelling in such diverse fields as sociology, education, psychology, economics, management and medical sciences. In addition to an extension of its application area, Structural Equation Modelling also features a continual renewal and extension of its theoretical background. The sixteen contributions to this book, written by experts from many countries, present important new developments and interesting applications in Structural Equation Modelling. The book addresses methodologists and statisticians professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved in their formulation. In addition, the book offers applied researchers new ideas about the use of Structural Equation Modeling in solving their problems. Finally, methodologists, mathematicians and applied researchers alike are addressed, who simply want to update their knowledge of recent approaches in data analysis and mathematical modelling.
    Note: 1: Theoretical Developments -- 1. Statistical Power in PATH Models for Small Sample Sizes -- 2. SEM State Space Modeling of Panel Data in Discrete and continuous Time and its Relationship to Traditional State Space Modeling -- 3. Thurstone’s Case V Model: a Structural Equations Modeling Perspective -- 4. Evaluating Uncertainty of Model Acceptability in Empirical Applications: A Replacement Approach -- 5. Improved Analytic Interval Estimation of Scale Reliability -- 6. A Component Analysis Approach towards Multisubject Multivariate Longitudinal Data Analysis -- 7. Least Squares Optimal Scaling for Partially Observed Linear Systems -- 8. Multilevel Structural Equation Models: the Limited Information Approach and the Multivariate Multilevel Approach -- 9. Latent Differential Equation Modeling with Multivariate MultiOccasion Indicators -- 2: Applications -- 10. Varieties of Causal Modeling: How Optimal Research Design Varies by Explanatory Strategy -- 11. Is it Possible to Feel Good and Bad at the Same Time? New Evidence on the Bipolarity of Mood-State Dimensions -- 12. Development of a Short Form of the Eysenck Personality Profiler via Structural Equation Modeling -- 13. Methodological Issues in the Application of the Latent Growth Curve Model -- 14. Modeling Longitudinal Data of an Intervention Study on Travel Model Choice: Combining Latent Growth Curves and Autoregressive Models -- 15. Methods for Dynamic Change Hypotheses -- 16. Modeling Latent Trait-Change.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9789048165490
    Language: English
    DOI: 10.1007/978-1-4020-1958-6
    URL: http://dx.doi.org/10.1007/978-1-4020-1958-6
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