Abstract
Advances in computing have made possible new latent variable methods that were not possible even 5 years ago. Network analysis and machine learning offer some of the most compelling computationally intensive approaches to data analysis. They have achieved objectives—playing chess and go, face and voice recognition, intelligent response to queries, and more—that statisticians might only have dreamt of 20 years ago. One surprising consequence of this intense investment in computationally intensive data analytics has been the surprise appearance of latent constructs that researchers had not hypothesized in advance. These emergent properties represent a whole new landscape for inquiry, theory-building, and latent variable analysis.
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Westland, J.C. (2019). Frontiers in Latent Variable Analysis. In: Structural Equation Models. Studies in Systems, Decision and Control, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-12508-0_8
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DOI: https://doi.org/10.1007/978-3-030-12508-0_8
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