Finding Structures of Interest in a Large Data Set Using Factor Analysis

Authors

  • Peter Filzmoser Department of Statistics and Probability Theory, Vienna University of Technology, AUSTRIA

DOI:

https://doi.org/10.17713/ajs.v26i2.548

Abstract

In this paper we introduce a statistical method which can be used in combination with principal component analysis or factor analysis. Certain variables of a large data set which are of interest can be selected in order to calculate loadings and scores of these variables. We describe how the remaining variables of the data set can be presented in the previously extracted factor space. Furthermore, a possibility for the representation of the results is shown which is helpful for the interpretation.

References

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P. Filzmoser. Principal Planes. PhD thesis, Dept. of Statistics and Prob. Th., Vienna University of Technology, 1996. Unpublished.

K.R. Gabriel. The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58(3):453–467, 1971.

H.H. Harman. Modern Factor Analysis. The University of Chicago Press, Chicago and London, 2nd edition, 1967.

D.N. Lawley and A.E. Maxwell. Factor Analysis as a Statistical Method. Butterworths, London, 1971.

K.V. Mardia, J.T. Kent, and J.M. Bibby. Multivariate Analysis. Acad. Press, London, 1979.

STUDIA and ALBTUM. External service of the rural agriculture in Bavaria. Technical report, STUDIA - Research Group for International Analyses, Schlierbach; ALBTUMProfessorship

for Applied Agricultural Business Economics, Freising-Weihenstephan, Munich University of Technology, 1993. (in German).

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Published

2016-04-03

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Section

Articles

How to Cite

Finding Structures of Interest in a Large Data Set Using Factor Analysis. (2016). Austrian Journal of Statistics, 26(2), 27–34. https://doi.org/10.17713/ajs.v26i2.548