Sequential Bayesian Ability Estimation Applied to Mixed-Format Item Tests.

ABSTRACT: Large-scale tests often contain mixed-format items, such as when multiple-choice (MC) items and constructed-response (CR) items are both contained in the same test. Although previous research has analyzed both types of items simultaneously, this may not always provide the best estimate of ability. In this paper, a two-step sequential Bayesian (SB) analytic method under the concept of empirical Bayes is explored for mixed item response models. This method integrates ability estimates from different item formats. Unlike the empirical Bayes method, the SB method estimates examinees' posterior ability parameters with individual-level sample-dependent prior distributions estimated from the MC items. Simulations were used to evaluate the accuracy of recovery of ability and item parameters over f

SUBMITTER: Xiong J 

PROVIDER: S-EPMC10552734 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature