Some recent Developments in Factor Analysis and the Search for proper Communalities

  • Jos M. F. ten Berge
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


This paper describes recent results on factor analytic theory which involve the so-called Ledermann bound, and discusses theoretical properties of Minimum Rank Factor Analysis as an alternative to Iterative Principal Factor Analysis and exploratory Maximum Likelihood Factor Analysis. In terms of the residual eigenvalues, the three methods have closely related object functions, and will often give highly similar solutions in practice. Nevertheless, there are important differences between the methods. The most notable points are that Maximum Likelihood Factor Analysis is a method of fitting a statistical model, and that Minimum Rank Factor Analysis yields communalities in the classical sense, thus showing how much of the common variance is explained with any given number of factors.

Key words

Factor analysis proper solutions Ledermann bound 


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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Jos M. F. ten Berge
    • 1
  1. 1.Heijmans InstituteUniversity of GroningenGroningenThe Netherlands

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