The unival package is designed to help researchers decide between unidimensional and correlated factors solutions in the factor analysis of psychometric measures. The novelty of the approach is its use of external information, in which multiple factor scores and general factor scores are related to relevant external variables or criteria. The unival package’s implementation comes from a series of procedures put forward by Ferrando and Lorenzo-Seva (2019) and new methodological developments proposed in this article. We assess models fitted using unival by means of a simulation study extending the results obtained in the original proposal. Its usefulness is also assessed through a real-world data example. Based on these results, we conclude unival is a valuable tool for use in applications in which the dimensionality of an item set is to be assessed.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2019-040.zip
unival, stats, optimbase, psych, mirt
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For attribution, please cite this work as
Ferrando, et al., "unival: An FA-based R Package For Assessing Essential Unidimensionality Using External Validity Information", The R Journal, 2019
BibTeX citation
@article{RJ-2019-040,
author = {Ferrando, Pere J. and Lorenzo-Seva, Urbano and Navarro-Gonzalez, David},
title = {unival: An FA-based R Package For Assessing Essential Unidimensionality Using External Validity Information},
journal = {The R Journal},
year = {2019},
note = {https://doi.org/10.32614/RJ-2019-040},
doi = {10.32614/RJ-2019-040},
volume = {11},
issue = {1},
issn = {2073-4859},
pages = {427-436}
}