elisr: Exploratory Likert Scaling
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.
| Version: |
0.1.1 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
stats (≥ 4.0.0) |
| Suggests: |
covr, devtools, knitr, pkgdown, psych, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2021-05-15 |
| DOI: |
10.32614/CRAN.package.elisr |
| Author: |
Steven Bißantz [aut, cre],
Thomas Müller-Schneider [ctb] |
| Maintainer: |
Steven Bißantz <steven.bissantz at gmail.com> |
| BugReports: |
https://github.com/sbissantz/elisr/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/sbissantz/elisr |
| NeedsCompilation: |
no |
| Language: |
en, de |
| Materials: |
README, NEWS |
| CRAN checks: |
elisr results |
Documentation:
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