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.

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Springer Verlag GmbH
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Contributors Preface PART 1: THEORETICAL DEVELOPMENTS 1. Statistical Power in PATH Models for Small Sample Sizes, Ab Mooijaart and Kees van Montfort 2. SEM State Space Modeling of Panel Data in Discrete and continuous Time and its Relationship to Traditional State Space Modeling, Johan Oud 3. Thurstone¿s Case V Model: a Structural Equations Modeling Perspective, Albert Maydeu-Olivares 4. Evaluating Uncertainty of Model Acceptability in Empirical Applications: A Replacement Approach, Luigi Lombardi, Massimiliano Pastore and Massimo Nucci 5. Improved Analytic Interval Estimation of Scale Reliability, Tenko Raykov and Spiridon Penev 6. A Component Analysis Approach towards Multisubject Multivariate Longitudinal Data Analysis, Marieke Timmerman 7. Least Squares Optimal Scaling for Partially Observed Linear Systems, Jan De Leeuw 8. Multilevel Structural Equation Models: the Limited Information Approach and the Multivariate Multilevel Approach, Joop Hox and Cora Maas 9. Latent Differential Equation Modeling with Multivariate Multi Occasion Indicators, Steve Boker, Michael Neale and Joseph Rausch PART 2: APPLICATIONS 10. Varieties of Causal Modeling: How Optimal Research Design Varies by Explanatory Strategy, Keith Markus 11. Is it Possible to Feel Good and Bad at the Same Time? New Evidence on the Bipolarity of Mood-State Dimensions, Rolf Steyer and Katrin Riedl 12. Development of a Short Form of the Eysenck Personality Profiler via Structural Equation Modeling, K.V. Petrides, Chris Jackson, Adrian Furnham and Stephen Levine 13. Methodological Issues in the Application of the Latent Growth Curve Model, Reinoud Stoel, Godfried van den Wittenboer and Joop Hox 14. Modeling Longitudinal Data of an Intervention Study on Travel Model Choice: Combining Latent Growth Curves and Autoregressive Models, Eldad Davidov, Peter Schmidt and Sebastian Bamberg 15. Methods for Dynamic Change Hypotheses, John Mc Ardle and Fumiaki Hamagami 16. Modeling Latent Trait-Change, Rolf Steyer, Sindy Krambeer and Wolfgang Hannöver