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Recent Developments on Structural Equation Models

Theory and Applications

  • Book
  • © 2004

Overview

Editors:
  1. Kees Montfort

    1. Free University Amsterdam, Amsterdam, The Netherlands

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  2. Johan Oud

    1. University of Nijmegen, Nijmegen, The Netherlands

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    You can also search for this editor in PubMed   Google Scholar

  3. Albert Satorra

    1. Universitat Pompeu Fabra, Barcelona, Spain

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  • Presents important new developments and interesting applications

Part of the book series: Mathematical Modelling: Theory and Applications (MMTA, volume 19)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-xv
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  2. Theoretical Developments

    1. Statistical Power in PATH Models for Small Sample Sizes

      • Ab Mooijaart, Kees van Montfort
      Pages 1-11

    2. SEM State Space Modeling of Panel Data in Discrete and Continuous Time and its Relationship to Traditional State Space Modeling

      • Johan Oud
      Pages 13-40

    3. Thurstone’s Case V Model: A Structural Equations Modeling Perspective

      • Albert Maydeu-Olivares
      Pages 41-67

    4. Evaluating Uncertainty of Model Acceptability in Empirical Applications: A Replacement Approach

      • Luigi Lombardi, Massimiliano Pastore, Massimo Nucci
      Pages 69-82

    5. Improved Analytic Interval Estimation of Scale Reliability

      • Tenko Raykov, Spiridon Penev
      Pages 83-93

    6. A Component Analysis Approach Towards Multisubject Multivariate Longitudinal Data Analysis

      • Marieke Timmerman
      Pages 95-119

    7. Least Squares Optimal Scaling of Partially Observed Linear Systems

      • Jan De Leeuw
      Pages 121-134

    8. Multilevel Structural Equation Models: the Limited Information Approach and the Multivariate Multilevel Approach

      • Joop Hox, Cora Maas
      Pages 135-149

    9. Latent Differential Equation Modeling with Multivariate Multi-Occasion Indicators

      • Steven Boker, Michael Neale, Joseph Rausch
      Pages 151-174

  3. Applications

    1. Varieties of Causal Modeling: How Optimal Research Design Varies by Explanatory Strategy

      • Keith Markus
      Pages 175-196

    2. Is it Possible to Feel Good and Bad at the Same Time? New Evidence on the Bipolarity of Mood-state Dimensions

      • Rolf Steyer, Katrin Riedl
      Pages 197-220

    3. Development of a Short Form of the Eysenck Personality Profiler via Structural Equation Modeling

      • K. V. Petrides, Chris J. Jackson, Adrian Furnham, Stephen Levine
      Pages 221-239

    4. Methodological Issues in the Application of the Latent Growth Curve Model

      • Reinoud D. Stoel, Godfried van den Wittenboer, Joop Hox
      Pages 241-261

    5. Modeling Longitudinal Data of an Intervention Study on Travel Model Choice: Combining Latent Growth Curves and Autoregressive Models.

      • Eldad Davidov, Peter Schmidt, Sebastian Bamberg
      Pages 263-293

    6. Methods for Dynamic Change Hypotheses

      • John McArdle, Fumiaki Hamagami
      Pages 295-335

    7. Modeling Latent Trait-Change

      • Rolf Steyer, Sindy Krambeer, Wolfgang Hannöver
      Pages 337-357

  4. Back Matter

    Pages 359-360
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Keywords

About this book

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.

Editors and Affiliations

  • Free University Amsterdam, Amsterdam, The Netherlands

    Kees Montfort

  • University of Nijmegen, Nijmegen, The Netherlands

    Johan Oud

  • Universitat Pompeu Fabra, Barcelona, Spain

    Albert Satorra

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