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ERIC Number: EJ1214809
Record Type: Journal
Publication Date: 2019-Jun
Pages: 31
Abstractor: As Provided
ISSN: ISSN-1076-9986
A Longitudinal Higher-Order Diagnostic Classification Model
Zhan, Peida; Jiao, Hong; Liao, Dandan; Li, Feiming
Journal of Educational and Behavioral Statistics, v44 n3 p251-281 Jun 2019
Providing diagnostic feedback about growth is crucial to formative decisions such as targeted remedial instructions or interventions. This article proposed a longitudinal higher-order diagnostic classification modeling approach for measuring growth. The new modeling approach is able to provide quantitative values of overall and individual growth by constructing a multidimensional higher-order latent structure to take into account the correlations among multiple latent attributes that are examined across different occasions. In addition, potential local item dependence among anchor (or repeated) items can be taken into account. Model parameter estimation is explored in a simulation study. An empirical example is analyzed to illustrate the applications and advantages of the proposed modeling approach.
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: Elementary Education; Grade 8; Junior High Schools; Middle Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: China
Grant or Contract Numbers: N/A