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Principal Components Analysis and Factorial Analysis to Measure Latent Variables in a Quantitative Research: A Mathematical Theoretical Approach
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Principal Components Analysis and Factorial Analysis to Measure Latent Variables in a Quantitative Research: A Mathematical Theoretical Approach

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Abstract:

The aim of this paper focuses on showing how the factorial analysis and principal components analysis are useful for measuring latent variables in a concise way and safely as a help to building for new concepts and theories.

Info:

Periodical:
The Bulletin of Society for Mathematical Services and Standards (Volume 7)
Pages:
3-12
DOI:
https://doi.org/10.18052/www.scipress.com/BSMaSS.7.3
Citation:
A. García-Santillán et al., "Principal Components Analysis and Factorial Analysis to Measure Latent Variables in a Quantitative Research: A Mathematical Theoretical Approach", The Bulletin of Society for Mathematical Services and Standards, Vol. 7, pp. 3-12, 2013
Online since:
September 2013
Authors:
Arturo García-Santillán, Milka Escalera-Chávez, Francisco Venegas-Martínez
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Distribution:
Open Access

Creative Commons License
This work is licensed under a
Creative Commons Attribution 4.0 International License

References:

Carrasco-Arroyo, S. (2012) Apuntes de Análisis Factorial [Notes for Analysis Factorial] Universidad de Valencia.

García-Santillán, A. et al (2013). Cognitive, Affective and Behavioral Components that explain Attitude toward Statistics. Journal of Mathematics Research. Vol 4, No. 5, October 2012 pp.8-16. (2012) URL: http: /dx. doi. org/10. 5539/jmr. v4n5p8.

García-Santillán, Venegas-Martínez and Escalera-Chávez (2013).

Hair, J. Anderson, R. (2001). Análisis Multivariante. Prentice Hall.

Wulder, M. (2013) A Practical Guide to the Use of Selected Multivariate Statistics. CanadianForest Service, Pacific Forestry Centre, Victoria, Canada.

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