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ERCIM Working Group

Computing & Statistics

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Latent Variable and Structural Equation Models


Latent variable and structural equation models have many different aims. Educational researchers and psychometricians use them as a tool for constructing measurement scales, calibrating questions and scoring individuals. Social and medical scientists use them in an exploratory fashion for explaining interrelationships among a number of observed variables using a smaller than the observed number latent variables. Political scientists and sociologists use them for verifying or disputing a sociological or political theory.


Recent, theoretical and methodological advances (multilevel structures, longitudinal data, robust methods, nonlinear models, missing values) together with the computational advancements allow complex social phenomena to be disentangled and described by structural equation models.


The track focuses on theoretical and applied developments in the area of latent variable and structural equation modelling.


Co-Chairs:

Irini Moustaki, Athens University of Economics and Business, Greece. E-mail: Send

Members

    1. Silvia Cagnone, University of Bologna, Italy.
    2. Cees Glas, University of Twente, Netherlands.
    3. Leonardo Grilli, University of Florence, Italy.
    4. Karl Joreskog, University of Uppsala, Sweden.
    5. Albert Maydeus-Olivares, University of Barcelona, Spain.
    6. Stefania Mignani, University of Bologna, Italy.
    7. Irini Moustaki, Athens University of Economics and Business, Greece.
    8. Carla Rampichini, University of Florence, Italy.
    9. Albert Satorra, University of Pompeu Fabra University, Spain.
    10. Anders Skrondal, London School of Economics, UK.
    11. Marieke Timmerman, University of Groningen, Netherlands.
    12. Bernard Veldkamp, University of Twente, Netherlands.
    13. Jeroen Vermunt, University of Tilburg, Netherlands.
    14. Fan Yang-Wallentin, University of Uppsala, Sweden.

Created by Computing & Statistics Working Group 2007