Revised Parallel Analysis with non-normal ability and a guessing parameter
Publication Date
2019
Document Type
Article
Abstract
Previous work showing that revised parallel analysis can be effective with dichotomous items has used a 2-parameter model and normally-distributed abilities. In this study, both 2-parameter and 3-parameter models were used with normally-distributed and skewed ability distributions. Relatively minor skew and kurtosis in the underlying ability distribution had almost no effect on Type I error for unidimensional data and reduced power for 2-dimensionsal data slightly with smaller sample sizes of 400. Using a 2-parameter model on 3-parameter data produced dramatically increased rejection rates for the unidimensional data. Using the correct 3-parameter model reduced the unidimensional rejection rates, but yielded lower power than the 2-parameter data in some conditions.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
DeMars, C. E. (2019). Revised Parallel Analysis with non-normal ability and a guessing parameter. Educational and Psychological Measurement, 79, 151-169. doi: 10.1177/0013164418767009
