Local homogeneity in latent trait models. A characterization of the homogeneous monotone IRT model

DOI10.1007/BF02294649zbMath0795.62101MaRDI QIDQ1309413

Jules L. Ellis, Arnold L. van den Wollenberg

Publication date: 18 September 1994

Published in: Psychometrika (Search for Journal in Brave)

zbMATH Keywords

local homogeneityunidimensionallatent trait modelslocal independencemonotonitybinary itemshomogeneous monotone item response theory modelpairwise nonnegative associationsubpopulation invariance

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Related Items (11)

A multidimensional item response model: Constrained latent class analysis using the Gibbs sampler and posterior predictive checks ⋮ Stochastic ordering using the latent trait and the sum score in polytomous IRT models ⋮ Some remarks on Scheiblechner's treatment of ISOP models ⋮ Tail-measurability in monotone latent variable models ⋮ Polytomous IRT models and monotone likelihood ratio of the total score ⋮ Stochastic order in dichotomous item response models for fixed, adaptive, and multidimensional tests ⋮ Additive conjoint isotonic probabilistic models (ADISOP) ⋮ The person response function as a tool in person-fit research ⋮ Mokken scale analysis for dichotomous items using marginal models ⋮ On the use, the misuse, and the very limited usefulness of Cronbach's alpha ⋮ The reliability factor: modeling individual reliability with multiple items from a single assessment

Cites Work

• Conditional association and unidimensionality in monotone latent variable models
• Testing the conditional independence and monotonicity assumptions of item response theory
• When are item response models consistent with observed data?
• Two new test statistics for the Rasch model
• On the sampling theory foundations of item response theory models
• A new item response theory modeling approach with applications to unidimensionality assessment and ability estimation
• A nonparametric approach for assessing latent trait unidimensionality
• Subjective Probability and Expected Utility without Additivity
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