Model Evaluation and Multiple Strategies in Cognitive Diagnosis: An Analysis of Fraction Subtraction Data

By Jimmy de la Torre, J. Douglas. 2008

160 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5a5d73feb5ceece81ea644653aa060b62509cf1e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Y. Park
2. Chun Wang
3. Wei Tian
4. Chia-Yi Chiu
5. Yanlou Liu
6. Young-Sun Lee
7. Tao Xin
8. L. DeCarlo

In Management Science and Operations Research

1. Chia-Yi Chiu
2. Wei Tian
3. Yanlou Liu
4. Tao Xin
5. Y. Park
6. Young-Sun Lee
7. Chun Wang
8. L. DeCarlo

In Statistics and Probability

1. Young-Sun Lee
2. Y. Park
3. Chun Wang
4. Wei Tian
5. Chia-Yi Chiu
6. Yanlou Liu
7. Tao Xin
8. L. DeCarlo

Citations in the corpus

• Bayesian Inference and Application of Robust Growth Curve Models Using Student's t Distribution (2013, unknown): “Furthermore, as pointed out by de la Torre and Douglas (2008), the use of posterior mean in constructing EAIC and EBIC also needs further justification.”
• An Application of M2 Statistic to Evaluate the Fit of Cognitive Diagnostic Models (2016, methodology): “This data set has been a commonly used example in cognitive diagnosis literature (e.g., DeCarlo, 2010; de la Torre, 2009, 2011; de la Torre & Douglas, 2008; Henson et al., 2009).”
• A Note on Comparing Examinee Classification Methods for Cognitive Diagnosis Models (2011, methodology): “(We note that running 25 replications of a simulation experiment has been deemed adequate for investigating examinee classification accuracy and item parameter estimation in previous studies; de la Torre & Douglas, 2004, 2008.)”
• A Cognitive Diagnostic Modeling of Attribute Mastery in Massachusetts, Minnesota, and the U.S. National Sample Using the TIMSS 2007 (2011, methodology): “Furthermore, the multiple-strategy DINA model (de la Torre & Douglas, 2008), which extends the single-strategy DINA model to allow for multiple strategies, can be applied; this model would examine whether other methods of solving the items can better explain the results.”
• On the Analysis of Fraction Subtraction Data: The DINA Model, Classification, Latent Class Sizes, and the Q-Matrix (2011, methodology): “The DINA model has been fit within a fully Bayesian framework using Markov chain Monte Carlo (MCMC) methods (e.g., de la Torre & Douglas, 2004, 2008; Henson et al., 2009; Junker & Sijtsma, 2001).”
• Statistical Refinement of the Q-Matrix in Cognitive Diagnosis (2013, background): “…(MLE) procedures to estimate model parameters that are then used to assign examinees to proficiency classes (de la Torre, 2008, 2009, 2011; de la Torre & Douglas, 2008; Haertel, 1989; Hartz, Roussos, Henson, & Templin, 2005; Henson, Templin, & Willse, 2009; Junker & Sijtsma, 2001; Maris, 1999;…”