Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 0 |
| Since 2006 (last 20 years) | 3 |
Descriptor
| Computer Software | 3 |
| Monte Carlo Methods | 3 |
| Computation | 2 |
| Evaluation Methods | 2 |
| Item Response Theory | 2 |
| Markov Processes | 2 |
| Test Bias | 2 |
| Accuracy | 1 |
| Comparative Analysis | 1 |
| Computer Simulation | 1 |
| Correlation | 1 |
| More ▼ | |
Source
| Journal of Educational… | 3 |
Author
| Briggs, Derek C. | 1 |
| He, Wei | 1 |
| Jiao, Hong | 1 |
| Nanda, Alice O. | 1 |
| Oshima, T. C. | 1 |
| Raju, Nambury S. | 1 |
| Wang, Shudong | 1 |
| Wilson, Mark | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 3 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkJiao, Hong; Wang, Shudong; He, Wei – Journal of Educational Measurement, 2013
This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE)…
Descriptors: Computation, Item Response Theory, Models, Monte Carlo Methods
Briggs, Derek C.; Wilson, Mark – Journal of Educational Measurement, 2007
An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random…
Descriptors: Markov Processes, Generalizability Theory, Item Response Theory, Computation
Oshima, T. C.; Raju, Nambury S.; Nanda, Alice O. – Journal of Educational Measurement, 2006
A new item parameter replication method is proposed for assessing the statistical significance of the noncompensatory differential item functioning (NCDIF) index associated with the differential functioning of items and tests framework. In this new method, a cutoff score for each item is determined by obtaining a (1-alpha ) percentile rank score…
Descriptors: Evaluation Methods, Statistical Distributions, Statistical Significance, Test Bias
