Advertisement

Psychometrika

, Volume 6, Issue 1, pp 49–53 | Cite as

Maximum likelihood estimation and factor analysis

  • Gale Young
Article

Abstract

Fisher's method of maximum likelihood is applied to the problem of estimation in factor analysis, as initiated by Lawley, and found to lead to a generalization of the Eckart matrix approximation problem. The solution of this in a special case is applied to show how test fallability enters into factor determination, it being noted that the method of communalities underestimates the number of factors.

Keywords

Public Policy Maximum Likelihood Estimation Likelihood Estimation Statistical Theory Approximation Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Eckart, Carl and Young, Gale. The approximation of one matrix by another of lower rank.Psychometrika, 1936,1, 211–218.Google Scholar
  2. 2.
    Fisher, R. A. On the mathematical foundations of theoretical statistics.Phil. Trans. Roy. Soc. A., 1921,222, 309–368.Google Scholar
  3. 3.
    Fisher, R. A. Theory of statistical esitmation.Proc. Camb. Phil. Soc., 1925,22, 700–725.Google Scholar
  4. 4.
    Fisher, R. A. Inverse probability.Proc. Camb. Phil. Soc., 1930,26, 528–535.Google Scholar
  5. 5.
    Householder, A. S. and Young, Gale. Matrix approximation and latent roots.Amer. Math. Monthly, 1938,45, 165–171.Google Scholar
  6. 6.
    Lawley, D. N. The estimation of factor loadings by the method of maximum likelihood.Proc. Roy. Soc. of Edinburgh, 1939,60, Part 1, No. 6.Google Scholar
  7. 7.
    Young, Gale. Factor analysis and the index of clustering.Psychometrika. 1939,4, 201–208.Google Scholar

Copyright information

© Psychometric Society 1941

Authors and Affiliations

  • Gale Young
    • 1
  1. 1.Olivet CollegeUSA

Personalised recommendations