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Paganin, Sally; Paciorek, Christopher J.; Wehrhahn, Claudia; Rodríguez, Abel; Rabe-Hesketh, Sophia; de Valpine, Perry – Journal of Educational and Behavioral Statistics, 2023
Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions based on Dirichlet process mixtures (DPMs) offer a more flexible representation of the unknown distribution of the latent trait. However, the use of such models in the IRT…
Descriptors: Bayesian Statistics, Item Response Theory, Guidance, Evaluation Methods
Flournoy, Nancy – 1989
Designs for sequential sampling procedures that adapt to cumulative information are discussed. A familiar illustration is the play-the-winner rule in which there are two treatments; after a random start, the same treatment is continued as long as each successive subject registers a success. When a failure occurs, the other treatment is used until…
Descriptors: Algorithms, Evaluation Methods, Mathematical Models, Research Design
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Wong, S. K. M.; And Others – Journal of the American Society for Information Science, 1991
Discussion of user queries in information retrieval highlights the experimental evaluation of an adaptive linear model that constructs improved query vectors from user preference judgments on a sample set of documents. The performance of this method is compared with that of standard relevance feedback techniques. (28 references) (LRW)
Descriptors: Algorithms, Comparative Analysis, Evaluation Methods, Information Retrieval