Peer reviewed
Download full textERIC Number: EJ1401330
Record Type: Journal
Publication Date: 2023
Pages: 15
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-1531-7714
Using a Bayesian Estimation to Examine Attribute Hierarchies of the 2007 TIMSS Mathematics Test: A Demonstration Using R Packages
Hsu, Chia-Ling; Chen, Yi-Hsin; Wu, Yi-Jhen
Practical Assessment, Research & Evaluation, v28 n11 Article 11 2023
Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian estimation using freely available R packages, including CDM and R2"jags." We illustrated a step-by-step procedure in R with an eighth-grade mathematics test from the 2007 Trends in International Mathematics and Science Study (TIMSS).
Descriptors: Bayesian Statistics, Computation, International Assessment, Achievement Tests, Mathematics Achievement, Mathematics Tests, Classification, Grade 8, Computer Software, Models
Center for Educational Assessment. 813 North Pleasant Street, Amherst, MA 01002. e-mail: pare@umass.edu; Tel: 413-577-2180; Web site: https://scholarworks.umass.edu/pare
Publication Type: Journal Articles; Reports - Research
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 - Assessments and Surveys: Trends in International Mathematics and Science Study
Grant or Contract Numbers: N/A
