Complex Latent Variable Modeling in Educational Assessment. Issue 5 (27th May 2016)

• Record Type: Journal Article
• Authors: Fox, Jean-Paul; Marsman, Maarten; Mulder, Joris; Verhagen, Josine
• Is Part Of: Communications in statistics. Volume 45:Issue 5(2016)
• Page Start: 1499
• Page End: 1510
• Publication Date: 2016-05-27
• Subjects: Bayes factor -- Bayesian modeling -- Latent variable models -- MCMC; 6207 -- 62F15 -- 62F99 -- 62H25; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2014.939518
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract : Bayesian item response theory models have been widely used in different research fields. They support measuring constructs and modeling relationships between constructs, while accounting for complex test situations (e.g., complex sampling designs, missing data, heterogenous population). Advantages of this flexible modeling framework together with powerful simulation-based estimation techniques are discussed. Furthermore, it is shown how the Bayes factor can be used to test relevant hypotheses in assessment using the College Basic Academic Subjects Examination (CBASE) data.