Results 161 to 170 of about 13,881,053 (181)

A Copula Model for Residual Dependency in DINA Model

2019
Cognitive diagnosis models (CDMs) have been received the increasing attention by educational and psychological assessment. In practice, most CDMs are not robust to violations of local item independence. Many approaches have been proposed to deal with the local item dependence (LID), such as conditioning on other responses and additional random effects (
Zhihui Fu, Ya-Hui Su, Jian Tao
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Q-matrix learning and DINA model parameter estimation

2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC), 2016
The DINA model is one of the most widely used models in cognitive and skills diagnosis, and several algorithms have been developed for estimating the model parameters. However, since the parameter space is very large and has a mix of binary variables, even medium-sized testing is extremely challenging.
Yuan Sun 0006, Shiwei Ye, Guiping Su, Yi Sun   +3 more
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Estimating the DINA model parameters using the No‐U‐Turn Sampler

Biometrical Journal, 2017
AbstractThe deterministic inputs, noisy, “and” gate (DINA) model is a popular cognitive diagnosis model (CDM) in psychology and psychometrics used to identify test takers' profiles with respect to a set of latent attributes or skills. In this work, we propose an estimation method for the DINA model with the No‐U‐Turn Sampler (NUTS) algorithm, an ...
Marcelo A. da Silva, Eduardo S. B. de Oliveira, Alina A. von Davier, Jorge L. Bazán   +3 more
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A Bayesian approach for the G-DINA model

Brazilian Journal of Probability and Statistics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fernandes, Renato, Bazán, Jorge Luis, Cúri, Mariana   +2 more
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Parameter Invariance and Skill Attribute Continuity in the DINA Model

Journal of Educational Measurement, 2018
AbstractCognitive diagnosis models (CDMs) typically assume skill attributes with discrete (often binary) levels of skill mastery, making the existence of skill continuity an anticipated form of model misspecification. In this article, misspecification due to skill continuity is argued to be of particular concern for several CDM applications due to the ...
Daniel M. Bolt, Jee‐Seon Kim
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Bayesian Estimation of the DINA Model With Gibbs Sampling

Journal of Educational and Behavioral Statistics, 2015
A Bayesian model formulation of the deterministic inputs, noisy “and” gate (DINA) model is presented. Gibbs sampling is employed to simulate from the joint posterior distribution of item guessing and slipping parameters, subject attribute parameters, and latent class probabilities.
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A Gibbs sampling algorithm that estimates the Q-matrix for the DINA model

Journal of Mathematical Psychology, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The impact of missingness to the G-DINA Model

2017
Missing responses happen when an examinee misses some items which results in an incomplete data. In this study, the impact of non-ignorable missingness to a general cognitive diagnostic model, the G-DINA model, was detected in terms of the effects on both classification rate and parameter estimation.
de la Torre, J, Sun, Y
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Application of the DINA Model Framework to Enhance Assessment and Learning

2012
This chapter introduces cognitive diagnosis models as a component of an alternative psychometric framework for diagnostic modeling and assessment and contrasts them to traditional item response models. The focus of this chapter is on the family of cognitive diagnosis models which represent various formulations and extensions of the deterministic, input,
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A Polytomous Cognitive Diagnosis Model: P- DINA Model

Acta Psychologica Sinica, 2011
Dong-Bo TU, Yan CAI, Hai-Qi DAI, Shu-Liang DING   +3 more
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