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Rnest: An R Package for the Next Eigenvalue Sufficiency Test for Factor Analysis
1Département des Sciences humaines, Lettres et Communication, Université TÉLUQ, Montréal, Canada.
Abstract:
To address the challenge of determining the number of factors to retain in exploratory factor analysis, a plethora of techniques, called stopping rules, has been developed, compared and widely used among researchers. Despite no definitive solution to this key issue, the recent Next Eigenvalue Sequence Test (NEST) showed interesting properties, such as being theoretically grounded in the factor analysis framework, robustness to cross loadings, a low false positive rate, sensitive to small but true factors, and better accuracy and unbiased compared to traditional stopping rules. Despite these strengths, there is no existing software readily available for researcher. These considerations have led to the development of the R package Rnest. This paper introduces NEST, presents the functionality of the Rnest package, and illustrates its workflow using a reproducible data example. By providing a practical and reliable approach to factor retention, this package aims to encourage its widespread adoption among practitioners, psychometricians, and methodological researchers conducting exploratory factor analyses.
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