An alternative to Exploratory Factor Analysis (EFA) for metrical data in R. Drawing on characteristics of classical test theory, Exploratory Likert Scaling (ELiS) supports the user exploring multiple one-dimensional data structures. In common research practice, however, EFA remains the go-to method to uncover the (underlying) structure of a data set. Orthogonal dimensions and the potential of overextraction are often accepted as side effects. As described in Müller-Schneider (2001) <doi:10.1515/zfsoz-2001-0404>), ELiS confronts these problems. As a result, 'elisr' provides the platform to fully exploit the exploratory potential of the multiple scaling approach itself.
Package details |
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Author | Steven Bißantz [aut, cre], Thomas Müller-Schneider [ctb] |
Maintainer | Steven Bißantz <steven.bissantz@gmail.com> |
License | GPL (>= 3) |
Version | 0.1.1 |
URL | https://github.com/sbissantz/elisr |
Package repository | View on CRAN |
Installation |
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