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.
|Number of pages||12|
|Journal||Communications in statistics. Simulation and computation|
|Publication status||Published - 27 May 2016|
- Bayes factor
- Bayesian modeling
- Latent variable models