Joint maximum likelihood estimation for diagnostic classification models

DOI10.1007/s11336-016-9534-9zbMath1367.62313OpenAlexW2530382185WikidataQ39297116 ScholiaQ39297116MaRDI QIDQ2364851

Chia-Yi Chiu, Yi Zheng, Robert A. Henson, Hans-Friedrich Köhn

Publication date: 25 July 2017

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-016-9534-9

zbMATH Keywords

cognitive diagnosisnonparametric classificationstatistical consistencyjoint maximum likelihood estimation

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to psychology (62P15)

Related Items (4)

Bridging parametric and nonparametric methods in cognitive diagnosis ⋮ A note on exploratory item factor analysis by singular value decomposition ⋮ Partial-mastery cognitive diagnosis models ⋮ Joint maximum likelihood estimation for high-dimensional exploratory item factor analysis

Uses Software

• CRAN
• Mplus
• BUGS
• Latent GOLD
• CDM
• NPCD

Cites Work

• A nonparametric approach to cognitive diagnosis by proximity to ideal response patterns
• The generalized DINA model framework
• Defining a family of cognitive diagnosis models using log-linear models with latent variables
• Cluster analysis for cognitive diagnosis: theory and applications
• Essential independence and likelihood-based ability estimation for polytomous items
• Consistency of nonparametric classification in cognitive diagnosis
• Hierarchical diagnostic classification models: a family of models for estimating and testing attribute hierarchies
• Item Response Theory
• Probability Inequalities for Sums of Bounded Random Variables
• 31A Review of Cognitively Diagnostic Assessment and a Summary of Psychometric Models
• 31B Some Notes on Models for Cognitively Based Skills Diagnosis
• Consistent Estimates Based on Partially Consistent Observations

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