Data analysis methods in optometry Part 8: Principal components analysis (PCA) and factor analysis (FA)

Richard A. Armstrong, Frank Eperjesi

Research output: Contribution to specialist publicationArticle

Abstract

PCA/FA is a method of analyzing complex data sets in which there are no clearly defined X or Y variables. It has multiple uses including the study of the pattern of variation between individual entities such as patients with particular disorders and the detailed study of descriptive variables. In most applications, variables are related to a smaller number of ‘factors’ or PCs that account for the maximum variance in the data and hence, may explain important trends among the variables. An increasingly important application of the method is in the ‘validation’ of questionnaires that attempt to relate subjective aspects of a patients experience with more objective measures of vision.
LanguageEnglish
Pages40-44
Number of pages5
Volume2008
No.March
Specialist publicationOptometry Today
Publication statusPublished - Mar 2008

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Factor Analysis
Principal Component Analysis
Data analysis
Questionnaire
Disorder

Keywords

  • analyzing complex data sets
  • pattern of variation

Cite this

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Data analysis methods in optometry Part 8: Principal components analysis (PCA) and factor analysis (FA). / Armstrong, Richard A.; Eperjesi, Frank.

In: Optometry Today, Vol. 2008, No. March, 03.2008, p. 40-44.

Research output: Contribution to specialist publicationArticle

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