Many standardized educational tests include groups of items based on a common stimulus, known as "testlets". Standard unidimensional item response theory (IRT) models are commonly used to model examinees' responses to testlet items. However, it is known that local dependence among testlet items can lead to biased item parameter estimates…

A basic consideration in large-scale assessments that use constructed response (CR) items, such as essays, is how to allocate the essays to the raters that score them. Designs that are used in practice are incomplete, in that each essay is scored by only a subset of the raters, and also unbalanced, in that the number of essays scored by each rater…

As is the case for any statistical model, a multidimensional latent growth model comes with certain requirements with respect to the data collection design. In order to measure growth, repeated measurements of the same set of individuals are required. Furthermore, the data collection design should be specified such that no individual is given the…

Maximum marginal likelihood estimation of multidimensional item response theory (IRT) models has been hampered by the calculation of the multidimensional integral over the ability distribution. However, the researcher often has a specific hypothesis about the conditional (in)dependence relations among the latent variables. Exploiting these…

Three multidimensional item response theory (IRT) models for testlet-based tests are described. In the bifactor model (Gibbons & Hedeker, 1992), each item measures a general dimension in addition to a testlet-specific dimension. The testlet model (Bradlow, Wainer, & Wang, 1999) is a bifactor model in which the loadings on the specific dimensions…

This paper presents an application of a stochastic approximation EM-algorithm using a Metropolis-Hastings sampler to estimate the parameters of an item response latent regression model. Latent regression models are extensions of item response theory (IRT) to a 2-level latent variable model in which covariates serve as predictors of the…

A general diagnostic model was used to specify and compare two multidimensional item-response-theory (MIRT) models for longitudinal data: (a) a model that handles repeated measurements as multiple, correlated variables over time (Andersen, 1985) and (b) a model that assumes one common variable over time and additional orthogonal variables that…

This paper examines item response theory (IRT) scale transformations and IRT scale linking methods used in the Non-Equivalent Groups with Anchor Test (NEAT) design to equate two tests, X and Y. It proposes a unifying approach to the commonly used IRT linking methods: mean-mean, mean-var linking, concurrent calibration, Stocking and Lord and…

Item parameter estimates vary for a variety of reasons, including estimation error, characteristics of the examinee samples, and context effects (e.g., item location effects, section location effects, etc.). Although we expect variation based on theory, there is reason to believe that observed variation in item parameter estimates exceeds what…