Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 2 |
Descriptor
Item Response Theory | 3 |
Monte Carlo Methods | 3 |
Psychometrics | 3 |
Test Length | 3 |
Algorithms | 1 |
Bayesian Statistics | 1 |
Comparative Analysis | 1 |
Computation | 1 |
Computer Simulation | 1 |
Computer Software | 1 |
Error of Measurement | 1 |
More ▼ |
Author
Due, Allan M. | 1 |
Kieftenbeld, Vincent | 1 |
Natesan, Prathiba | 1 |
Reise, Steven P. | 1 |
Sengul Avsar, Asiye | 1 |
Tavsancil, Ezel | 1 |
Publication Type
Journal Articles | 3 |
Reports - Evaluative | 2 |
Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Sengul Avsar, Asiye; Tavsancil, Ezel – Educational Sciences: Theory and Practice, 2017
This study analysed polytomous items' psychometric properties according to nonparametric item response theory (NIRT) models. Thus, simulated datasets--three different test lengths (10, 20 and 30 items), three sample distributions (normal, right and left skewed) and three samples sizes (100, 250 and 500)--were generated by conducting 20…
Descriptors: Test Items, Psychometrics, Nonparametric Statistics, Item Response Theory
Kieftenbeld, Vincent; Natesan, Prathiba – Applied Psychological Measurement, 2012
Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…
Descriptors: Test Length, Markov Processes, Item Response Theory, Monte Carlo Methods

Reise, Steven P.; Due, Allan M. – Applied Psychological Measurement, 1991
Previous person-fit research is extended through explication of an unexplored model for generating aberrant response patterns. The proposed model is then implemented to investigate the influence of test properties on the aberrancy detection power of a person-fit statistic. Difficulties of aberrancy detection are discussed. (SLD)
Descriptors: Algorithms, Computer Simulation, Item Response Theory, Mathematical Models