On the Relationship between the Higher-Order Factor Model and the Hierarchical Factor Model
1999/06/01 by Yiu-Fai Yung, Yiu‐Fai Yung, David Thissen +2 · 409 citations
Computer Science · Mathematics · #Artificial intelligence #Class (philosophy) #Computer science #Data mining #Econometrics #Factor (programming language) #Factor analysis #Hierarchical database model #Mathematics #Matrix Theory and Algorithms #Order (exchange) #Statistics #Transformation (genetics)
paper · doi:10.1007/bf02294531
published in Psychometrika 64(2), 113-128 (Springer Science+Business Media)
openalex publication_date 1999/06/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25
Abstract
The relationship between the higher-order factor model and the hierarchical factor model is explored formally. We show that the Schmid-Leiman transformation produces constrained hierarchical factor solutions. Using a generalized Schmid-Leiman transformation and its inverse, we show that for any unconstrained hierarchical factor model there is an equivalent higher-order factor model with direct effects (loadings) on the manifest variables from the higher-order factors. Therefore, the class of higher-order factor models (without direct effects of higher-order factors) is nested within the class of unconstrained hierarchical factor models. In light of these formal results, we discuss some implications for testing the higher-order factor model and the issue of general factor. An interesting aspect concerning the efficient fitting of the higher-order factor model with direct effects is noted.
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