Dimensionality assessment of ordered polytomous items with parallel analysis.
University of Groningen · Universitat Rovira i Virgili
Abstract
Parallel analysis (PA) is an often-recommended approach for assessment of the dimensionality of a variable set. PA is known in different variants, which may yield different dimensionality indications. In this article, the authors considered the most appropriate PA procedure to assess the number of common factors underlying ordered polytomously scored variables. They proposed minimum rank factor analysis (MRFA) as an extraction method, rather than the currently applied principal component analysis (PCA) and principal axes factoring. A simulation study, based on data with major and minor factors, showed that all procedures consistently point at the number of major common factors. A polychoric-based PA slightly…
Citation impact
- FWCI
- 24.28
- Percentile
- 100%
- References
- 58
Authors
2Topics & keywords
- Polychoric correlation
- Principal component analysis
- Statistics
- Mathematics
- Curse of dimensionality
- Polytomous Rasch model
- Ordinal data
- Econometrics