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Direct linkGierl, Mark J.; Leighton, Jacqueline P.; Tan, Xuan – Journal of Educational Measurement, 2006
DETECT, the acronym for Dimensionality Evaluation To Enumerate Contributing Traits, is an innovative and relatively new nonparametric dimensionality assessment procedure used to identify mutually exclusive, dimensionally homogeneous clusters of items using a genetic algorithm ( Zhang & Stout, 1999). Because the clusters of items are mutually…
Descriptors: Program Evaluation, Cluster Grouping, Evaluation Methods, Multivariate Analysis
Peer reviewedBejar, Isaac I. – Journal of Educational Measurement, 1980
Two procedures are presented for detecting violations of the unidimensionality assumption made by latent trait models without requiring factor analysis of inter-item correlation matrices. Both procedures require that departures from unidimensionality be hypothesized beforehand. This is usually possible in achievement tests where several content…
Descriptors: Achievement Tests, Bayesian Statistics, Cluster Grouping, Content Analysis
