The comparison of the scores obtained by Bayesian nonparametric model and classical test theory methods.

ABSTRACT: Bayesian Nonparametric (BNP) modelling can be used to obtain more detailed information in test equating studies and to increase the accuracy of equating by accounting for covariates. In this study, two covariates are included in the equating under the Bayes nonparametric model, one is continuous, and the other is discrete. Scores equated with this model were obtained for a single group design for a small group in the study. The equated scores obtained with the model were compared with the mean and linear equating methods in the Classical Test Theory. Considering the equated scores obtained from three different methods, it was found that the equated scores obtained with the BNP model produced a distribution closer to the target test. Even the classical methods will give a good result with t

SUBMITTER: Yurtcu M 

PROVIDER: S-EPMC10450720 | biostudies-literature | 2021 Jul-Sep

REPOSITORIES: biostudies-literature