Sparse versus simple structure loadings

Trendafilov, Nickolay T. and Adachi, Kohei (2015). Sparse versus simple structure loadings. Psychometrika, 80(3) pp. 776–790.

DOI: https://doi.org/10.1007/s11336-014-9416-y

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

Viewing alternatives

Metrics

Item Actions

Export

You can export this page using these formats Digital Object Identifier - DOI

About

• Item ORO ID
• 41222
• Item Type
• Journal Item
• ISSN
• 1860-0980
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  Sparse factor analysis with application to large data sets	RPG--2013--211	The Leverhulme Trust

• Keywords
• principal component analysis; factor analysis; orthogonal and oblique rotations; sparseness-inducing constraints; LASSO constraints; projected gradients
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 2014 The Psychometric Society
• Depositing User
• Nickolay Trendafilov