Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…

Effective educational measurement relies heavily on the curation of well-designed item pools. However, item calibration is time consuming and costly, requiring a sufficient number of respondents to estimate the psychometric properties of items. In this study, we explore the potential of six different large language models (LLMs; GPT-3.5, GPT-4,…

The problem of local item dependencies (LIDs) is very common in personality and attitude measures, particularly in those that measure narrow-bandwidth dimensions. At the structural level, these dependencies can be modeled by using extended factor analytic (FA) solutions that include correlated residuals. However, the effects that LIDs have on the…