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

Armstrong, Richard A. and Eperjesi, Frank (2008). Data analysis methods in optometry Part 8: Principal components analysis (PCA) and factor analysis (FA). Optometry Today, 2008 (March), pp. 40-44.

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.

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