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ERIC Number: EJ1427007
Record Type: Journal
Publication Date: 2024
Pages: 12
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0895-7347
EISSN: EISSN-1532-4818
Bayesian Maximal Reliability Evaluation Using Latent Variable Modeling
Tenko Raykov; George A. Marcoulides; Natalja Menold
Applied Measurement in Education, v37 n2 p165-176 2024
We discuss an application of Bayesian factor analysis for estimation of the optimal linear combination and associated maximal reliability of a multi-component measuring instrument. The described procedure yields point and credibility interval estimates of this reliability coefficient, which are readily obtained in educational and behavioral measurement research. In addition, the outlined method permits evaluation of the gain in measurement consistency resulting from utilizing the maximal reliability coefficient instead of the traditionally used overall sum score reliability. The discussed Bayesian inference approach is applicable with widely available software in empirical studies, and is illustrated using a data example.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A