A Nonparametric Multidimensional IRT Approach with Applications to Ability Estimation and Test Bias.
ILLINOIS UNIV AT URBANA PSYCHOMETRIC GROUP
Pagination or Media Count:
A determined case is made for the use of a nonparametric multidimensional monotonic IRT modeling framework with local independence replaced by the less restrictive assumption of essential independence. The concept of essential dimensionality is then introduced to count the number of dominant latent dimensions. Consequences of this more general approach include the consistent estimation of ability on a common scale using a natural class of estimators, uniqueness of the latent ability when essential unidimensionality holds, a theoretical treatment of test bias, an IRT based notion of validity, and a reassessment of the importance of the concept of item parameter invariance. Keywords Local independence Essential independence Essential trait Intrinsic ability scale Marginal item response function Latent dimensionality Multidimensionality Essential dimensionality Essential unidimensionality Item response theory Latent trait theory Ability estimation Consistent estimation Item parameter invariance Validity Linear formula scoring Nonparametric.
- Statistics and Probability