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Guo, Wenjing; Choi, Youn-Jeng – Educational and Psychological Measurement, 2023
Determining the number of dimensions is extremely important in applying item response theory (IRT) models to data. Traditional and revised parallel analyses have been proposed within the factor analysis framework, and both have shown some promise in assessing dimensionality. However, their performance in the IRT framework has not been…
Descriptors: Item Response Theory, Evaluation Methods, Factor Analysis, Guidelines
Woods, Carol M. – Applied Psychological Measurement, 2007
Ramsay curve item response theory (RC-IRT) was recently developed to detect and correct for nonnormal latent variables when unidimensional IRT models are fitted to data using maximum marginal likelihood estimation. The purpose of this research is to evaluate the performance of RC-IRT for Likert-type item responses with varying test lengths, sample…
Descriptors: Test Length, Item Response Theory, Sample Size, Comparative Analysis