Psychometrika. 2024 Aug 17. doi: 10.1007/s11336-024-09997-y. Online ahead of print.
ABSTRACT
A well-known person fit statistic in the item response theory (IRT) literature is the l z statistic (Drasgow et al. in Br J Math Stat Psychol 38(1):67-86, 1985). Snijders (Psychometrika 66(3):331-342, 2001) derived l z ∗ , which is the asymptotically correct version of l z when the ability parameter is estimated. However, both statistics and other extensions later developed concern either only the unidimensional IRT models or multidimensional models that require a joint estimate of latent traits across all the dimensions. Considering a marginalized maximum likelihood ability estimator, this paper proposes l zt and l zt ∗ , which are extensions of l z and l z ∗ , respectively, for the Rasch testlet model. The computation of l zt ∗ relies on several extensions of the Lord-Wingersky algorithm (1984) that are additional contributions of this paper. Simulation results show that l zt ∗ has close-to-nominal Type I error rates and satisfactory power for detecting aberrant responses. For unidimensional models, l zt and l zt ∗ reduce to l z and l z ∗ , respectively, and therefore allows for the evaluation of person fit with a wider range of IRT models. A real data application is presented to show the utility of the proposed statistics for a test with an underlying structure that consists of both the traditional unidimensional component and the Rasch testlet component.
PMID:39153026 | DOI:10.1007/s11336-024-09997-y
