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Factor Analysis as A Tool for Pattern Recognition in Biomedical Research: A Review with Application in R Software
Volume 15, Issue 4 (2017), pp. 615–630
Dimitris Panaretos   George Tzavelas   Malvina Vamvakari     All authors (4)

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https://doi.org/10.6339/JDS.201710_15(4).00003
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

Factor Analysis is one of the data mining methods that can be used to analyse, mainly large-scale, multi-variable datasets. The main objective of this method is to derive a set of uncorrelated variables for further analysis when the use of highly inter-correlated variables may give misleading results in regression analysis. In the light of the vast and broad advances that have occurred in factor analysis due largely to the advent of electronic computers, this article attempt to provide researchers with a simplified approach to comprehend how exploratory factors analysis work, and to provide a guide of application using R. This multivariate mathematical method is an important tool which very often used in the development and evaluation of tests and measures that can be used in biomedical research. The paper comes to the conclusion that the factor analysis is a proper method used in biomedical research, just because clinical readers can better interpret and evaluate their goal and results.

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Keywords
biostatistics exploratory factor analysis multivariate analysis pattern analysis R programming language

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Journal of data science

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