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Download full textGuo, Hongwen; Sinharay, Sandip – Educational Testing Service, 2011
Nonparametric, or kernel, estimation of item response curve (IRC) is a concern theoretically and operationally. Accuracy of this estimation, often used in item analysis in testing programs, is biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. In this study, we investigate…
Descriptors: Error of Measurement, Nonparametric Statistics, Item Response Theory, Computation
Rijmen, Frank – Educational Testing Service, 2009
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…
Descriptors: Item Response Theory, Models, Graphs, Comparative Analysis
von Davier, Matthias; Xu, Xueli; Carstensen, Claus H. – Educational Testing Service, 2009
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…
Descriptors: Models, Item Response Theory, Longitudinal Studies, Measurement
Sinharay, Sandip; Holland, Paul W. – Educational Testing Service, 2008
The nonequivalent groups with anchor test (NEAT) design involves missing data that are missing by design. Three popular equating methods that can be used with a NEAT design are the poststratification equating method, the chain equipercentile equating method, and the item-response-theory observed-score-equating method. These three methods each…
Descriptors: Equated Scores, Test Items, Item Response Theory, Data
