This review introduces classical item response theory (IRT) models as well as more
contemporary extensions to the case of multilevel, multidimensional, and mixtures of …

We present a flexible full-information approach to modeling multiple user-defined response
styles across multiple constructs of interest. The model is based on a novel parameterization …

The cross-classified data structure is ubiquitous in education, psychology, and health
outcome sciences. In these areas, assessment instruments that are made up of multiple …

Multilevel analyses are often used to estimate the effects of group-level constructs. However,
when using aggregated individual data (eg, student ratings) to assess a group-level …

In diagnostic classification models (DCMs), the Q matrix encodes in which attributes are
required for each item. The Q matrix is usually predetermined by the researcher but may in …

Identifying items with differential item functioning (DIF) in an assessment is a crucial step for
achieving equitable measurement. One critical issue that has not been fully addressed with …

The four-parameter logistic (4PL) Item Response Theory (IRT) model has recently been
reconsidered in the literature due to the advances in the statistical modeling software and …

The estimation of high-dimensional latent regression item response theory (IRT) models is
difficult because of the need to approximate integrals in the likelihood function. Proposed …

Random item effects item response theory (IRT) models, which treat both person and item
effects as random, have received much attention for more than a decade. The random item …

In the research reported here, we propose a new method for scale alignment and test
scoring in the context of supporting students with disabilities. In educational assessment …