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Random Intercept Item Factor Analysis

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  • ALBERTO MAYDEU

    ()
    (Instituto de Empresa)

Abstract

(WP 02/03 Clave pdf) The common factor model assumes a linear relation between the observed variables and a set of underlying latent traits. It also assumes that the linear coefficients, intercepts and slopes (factor loadings), linking the observed variables to the latent traits are fixed coefficients (i.e., common for all subjects). We partially relax the fixed coefficients assumption by letting the intercepts in the factor model change across subjects while keeping the factor loadings fixed.

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File URL: http://latienda.ie.edu/working_papers_economia/WP03-02.pdf
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Bibliographic Info

Paper provided by Instituto de Empresa, Area of Economic Environment in its series Working Papers Economia with number wp03-02.

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Length: 16 pages
Date of creation: Apr 2003
Date of revision:
Handle: RePEc:emp:wpaper:wp03-02

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Related research

Keywords: Difficulty factors; Life Orientation Test; LISREL; Random effects; Structural equation modeling;

References

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  1. Albert Satorra & Peter Bentler, 2001. "A scaled difference chi-square test statistic for moment structure analysis," Psychometrika, Springer, vol. 66(4), pages 507-514, December.
  2. Gerhard Arminger & Ronald Schoenberg, 1989. "Pseudo maximum likelihood estimation and a test for misspecification in mean and covariance structure models," Psychometrika, Springer, vol. 54(3), pages 409-425, September.
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Citations

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Cited by:
  1. Alberto Maydeu, 2008. "Modeling Preference Data," Working Papers Economia wp08-30, Instituto de Empresa, Area of Economic Environment.
  2. Camacho, N.M.A. & de Jong, M.G. & Stremersch, S., 2014. "The Effect of Customer Empowerment on Adherence to Expert Advice," ERIM Report Series Research in Management ERS-2014-005-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  3. Li Cai, 2010. "A Two-Tier Full-Information Item Factor Analysis Model with Applications," Psychometrika, Springer, vol. 75(4), pages 581-612, December.

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