TY - JOUR
T1 - Complex latent variable modeling in educational assessment
AU - Fox, J.-P.
AU - Marsman, M.
AU - Mulder, J.
AU - Verhagen, J.A.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
U2 - 10.1080/03610918.2014.939518
DO - 10.1080/03610918.2014.939518
M3 - Article
SN - 0361-0918
VL - 45
SP - 1499
EP - 1510
JO - Communications in Statistics: Part B: Simulation and Computation
JF - Communications in Statistics: Part B: Simulation and Computation
IS - 5
ER -