A General Bayesian Multidimensional Item Response Theory Model for Small and Large Samples.

ABSTRACT: Although item response theory (IRT) models such as the bifactor, two-tier, and between-item-dimensionality IRT models have been devised to confirm complex dimensional structures in educational and psychological data, they can be challenging to use in practice. The reason is that these models are multidimensional IRT (MIRT) models and thus are highly parameterized, making them only suitable for data provided by large samples. Unfortunately, many educational and psychological studies are conducted on a small scale, leaving the researchers without the necessary MIRT models to confirm the hypothesized structures in their data. To address the lack of modeling options for these researchers, we present a general Bayesian MIRT model based on adaptive informative priors. Simulations demonstrated th

SUBMITTER: Fujimoto KA 

PROVIDER: S-EPMC7307486 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature