arXiv subjects

Peida Zhan

Publications and source records attributed to Peida Zhan.

3 recordsLinked to original sources

arXiv2018

Using JAGS for Bayesian Cognitive Diagnosis Modeling: A Tutorial

In this article, the JAGS software program is systematically introduced to fit common Bayesian cognitive diagnosis models (CDMs), including the deterministic inputs, noisy "and" gate (DINA) model, the deterministic inputs, noisy "or" gate (DINO) model, the linear logistic model, the reduced reparameterized unified model (rRUM), and the log-linear CDM (LCDM). The unstructured latent structural model and the higher-order latent structural model are both introduced. We also show how to extend those models to consider the polytomous attributes, the testlet effect, and the longitudinal diagnosis. Finally, an empirical example is presented as a tutorial to illustrate how to use the JAGS codes in R.

stat.CO↗

arXiv2018

A Longitudinal Higher-Order Diagnostic Classification Model

Providing diagnostic feedback about growth is crucial to formative decisions such as targeted remedial instructions or interventions. This paper proposed a longitudinal higher-order diagnostic classification modeling approach for measuring growth. The new modeling approach is able to provide quantitative values of overall and individual growth by constructing a multidimensional higher-order latent structure to take into account the correlations among multiple latent attributes that are examined across different occasions. In addition, potential local item dependence among anchor (or repeated) items can also be taken into account. Model parameter estimation is explored in a simulation study. An empirical example is analyzed to illustrate the applications and advantages of the proposed modeling approach.

stat.ME↗

arXiv2018

A Multidimensional Hierarchical Framework for Modeling Speed and Ability in Computer-based Multidimensional Tests

In psychological and educational computer-based multidimensional tests, latent speed, a rate of the amount of labor performed on the items with respect to time, may also be multidimensional. To capture the multidimensionality of latent speed, this study firstly proposed a multidimensional log-normal response time (RT) model to consider the potential multidimensional latent speed. Further, to simultaneously take into account the response accuracy (RA) and RTs in multidimensional tests, a multidimensional hierarchical modeling framework was proposed. The framework is an extension of the van der Linden (2007; doi:10.1007/s11336-006-1478-z) and allows a "plug-and-play approach" with alternative choices of multidimensional models for RA and RT. The model parameters within the framework were estimated using the Bayesian Markov chain Monte Carlo method. The 2012 Program for International Student Assessment computer-based mathematics data were analyzed first to illustrate the implications and applications of the proposed models. The results indicated that it is appropriate to simultaneously consider the multidimensionality of latent speed and latent ability for multidimensional tests. A brief simulation study was conducted to evaluate the parameter recovery of the proposed model and the consequences of ignoring the multidimensionality of latent speed.

stat.ME↗