Journal
PSYCHOMETRIKA
Volume 69, Issue 1, Pages 81-99Publisher
PSYCHOMETRIC SOC
DOI: 10.1007/BF02295841
Keywords
path analysis with components; partial least squares; alternating least squares
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We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method avoids the principal limitation of partial least squares (i.e., the lack of a global optimization procedure) while fully retaining all the advantages of partial least squares (e.g., less restricted distributional assumptions and no improper solutions). The method is also versatile enough to capture complex relationships among variables, including higher-order components and multi-group comparisons. A straightforward estimation algorithm is developed to minimize the criterion.
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