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Computation of the covariance matrix implied by a recursive structural equation model with latent variables

Author

Listed:
  • Zouhair El Hadri

    (Mohammed V University in Rabat)

  • M’barek Iaousse

    (Hassan II University of Casablanca)

Abstract

Structural Equation Modelling is a multivariate technique that allows us to analyze causal relationships between hypothetical constructs, each measured by several observable variables. The computation of the covariance matrix implied by the model is a crucial step in the whole modelling process. In this paper, a new theorem for the computation of the implied covariance matrix is proposed. This theorem will be useful to find the classical Jöreskog’s formula. Besides, it will be the basis for introducing a new method for computation based on the Finite Iterative Method. Finally, theoretical and computational comparisons between the proposed method and Jöreskog’s formula are also discussed and illustrated.

Suggested Citation

  • Zouhair El Hadri & M’barek Iaousse, 2022. "Computation of the covariance matrix implied by a recursive structural equation model with latent variables," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4295-4311, December.
    • Handle: RePEc:spr:qualqt:v:56:y:2022:i:6:d:10.1007_s11135-022-01321-z
    DOI: 10.1007/s11135-022-01321-z
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    References listed on IDEAS

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    1. Pasquale Dolce & Natale Lauro, 2015. "Comparing maximum likelihood and PLS estimates for structural equation modeling with formative blocks," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 891-902, May.
    2. Jamshidian, Mortaza & Bentler, Peter M., 1993. "A modified Newton method for constrained estimation in covariance structure analysis," Computational Statistics & Data Analysis, Elsevier, vol. 15(2), pages 133-146, February.
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    Cited by:

    1. Seyid Abdellahi Ebnou Abdem & Zouhair El Hadri & M’barek Iaousse, 2024. "New lights on the correlation matrix implied by a recursive path model," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 119-139, February.

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