Sparse Versus Simple Structure Loadings

Nickolay Trendafilov () and Kohei Adachi

Psychometrika, 2015, vol. 80, issue 3, 776-790

Abstract: The component loadings are interpreted by considering their magnitudes, which indicates how strongly each of the original variables relates to the corresponding principal component. The usual ad hoc practice in the interpretation process is to ignore the variables with small absolute loadings or set to zero loadings smaller than some threshold value. This, in fact, makes the component loadings sparse in an artificial and a subjective way. We propose a new alternative approach, which produces sparse loadings in an optimal way. The introduced approach is illustrated on two well-known data sets and compared to the existing rotation methods. Copyright The Psychometric Society 2015

Keywords: principal component analysis; factor analysis; orthogonal and oblique rotations; sparseness-inducing constraints; LASSO constraints; projected gradients (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s11336-014-9416-y

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