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The Scree Test and the Number of Factors: a Dynamic Graphics Approach

Published online by Cambridge University Press:  17 March 2015

Rubén Daniel Ledesma*
Affiliation:
Universidad Nacional de Mar del Plata (Argentina)
Pedro Valero-Mora
Affiliation:
Universidad de Valencia (Spain)
Guillermo Macbeth
Affiliation:
Universidad Nacional de Entre Ríos (Argentina)
*
*Correspondence concerning this article should be addressed to Ruben D. Ledesma. Universidad Nacional de Mar del Plata & Consejo Nacional de Investigaciones Científicas y Técnicas. Rio Negro, 3922. 7600. Mar del Plata (Argentina). E-mail. rdledesma@conicet.gov.ar

Abstract

Exploratory Factor Analysis and Principal Component Analysis are two data analysis methods that are commonly used in psychological research. When applying these techniques, it is important to determine how many factors to retain. This decision is sometimes based on a visual inspection of the Scree plot. However, the Scree plot may at times be ambiguous and open to interpretation. This paper aims to explore a number of graphical and computational improvements to the Scree plot in order to make it more valid and informative. These enhancements are based on dynamic and interactive data visualization tools, and range from adding Parallel Analysis results to "linking" the Scree plot with other graphics, such as factor-loadings plots. To illustrate our proposed improvements, we introduce and describe an example based on real data on which a principal component analysis is appropriate. We hope to provide better graphical tools to help researchers determine the number of factors to retain.

Type
Research Article
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2015 

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