Mixture item response theory (MixIRT) models combine IRT models with latent class model
and assume that there exist latent subpopulations in the data. Identification of latent …

This study examines model selection indices for use with dichotomous mixture item
response theory (IRT) models. Five indices are considered: Akaike's information coefficient …

Cumulative sum (CUSUM) and change-point analysis (CPA) are two well-established
statistical process control methods to detect changes in a sequence. Both have been used in …

Even though Bayesian estimation has recently become quite popular in item response
theory (IRT), there is a lack of works on model checking from a Bayesian perspective. This …

An examinee faced with a test item will engage in solution behavior or rapid-guessing
behavior. These qualitatively different test-taking behaviors bias parameter estimates for …

Mixture item response theory models have been suggested as a potentially useful
methodology for identifying latent groups formed along secondary, possibly nuisance …

Change-point analysis (CPA) is a well-established statistical method to detect abrupt
changes, if any, in a sequence of data. In this paper, we propose a procedure based on CPA …

Adult assessments have evolved to keep pace with the changing nature of adult literacy and
learning demands. As the importance of information and communication technologies (ICT) …

Technical advances provide the possibility of capturing timing and process data as test
takers solve digital problems in computer-based assessments. The data collected in log …

The models used in this article are secondary dimension mixture models with the potential to
explain differential item functioning (DIF) between latent classes, called latent DIF. The focus …