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An Introduction to Structural Equation Models

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Book cover Structural Equation Models

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 22))

Abstract

Early twentieth century research into genetic pathways initiated a revolution on hybrid crops, industrial farming, and eugenics and initially motivated the work on structural equation models. Geneticist and statistician Sewall Wright’s seminal work in path analysis laid the groundwork for the Chicago and Scandinavian Schools of structural equation modeling. Though rooted in the natural sciences, structural equation models rose to prominence through their utility for determining relationships and structures of unobserved, latent constructs in the social sciences. Advances in computing in the 1970s gave the increasingly complex structural equation model methodologies the necessary capabilities to handle larger and larger datasets. Automation drove the move from the pairwise Pearsonian correlations of path analysis, to structures of canonical correlations in partial least squares path analysis, and finally to the full covariance structure methods of the Chicago and Scandinavian Schools.

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  1. Information & Decision Systems, University of Illinois at Chicago, Chicago, IL, USA

    J. Christopher Westland

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Westland, J.C. (2019). An Introduction to Structural Equation Models. In: Structural Equation Models. Studies in Systems, Decision and Control, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-12508-0_1

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