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) | 2 |
Descriptor
| Monte Carlo Methods | 3 |
| Program Effectiveness | 3 |
| Test Items | 3 |
| Item Response Theory | 2 |
| Simulation | 2 |
| Basic Skills | 1 |
| College Entrance Examinations | 1 |
| Comparative Analysis | 1 |
| Data Analysis | 1 |
| Evaluation Methods | 1 |
| Factor Analysis | 1 |
| More ▼ | |
Author
| Habing, Brian | 2 |
| Asparouhov, Tihomir | 1 |
| Finch, Holmes | 1 |
| Froelich, Amy G. | 1 |
| Muthen, Bengt O. | 1 |
| Nylund, Karen L. | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Evaluative | 3 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| SAT (College Admission Test) | 1 |
What Works Clearinghouse Rating
Peer reviewed
Direct linkFroelich, Amy G.; Habing, Brian – Applied Psychological Measurement, 2008
DIMTEST is a nonparametric hypothesis-testing procedure designed to test the assumptions of a unidimensional and locally independent item response theory model. Several previous Monte Carlo studies have found that using linear factor analysis to select the assessment subtest for DIMTEST results in a moderate to severe loss of power when the exam…
Descriptors: Test Items, Monte Carlo Methods, Form Classes (Languages), Program Effectiveness
Nylund, Karen L.; Asparouhov, Tihomir; Muthen, Bengt O. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study…
Descriptors: Test Items, Monte Carlo Methods, Program Effectiveness, Data Analysis
Finch, Holmes; Habing, Brian – Journal of Educational Measurement, 2005
This study examines the performance of a new method for assessing and characterizing dimensionality in test data using the NOHARM model, and comparing it with DETECT. Dimensionality assessment is carried out using two goodness-of-fit statistics that are compared to reference X[2] distributions. A Monte Carlo study is used with item parameters…
Descriptors: Program Effectiveness, Monte Carlo Methods, Item Response Theory, Comparative Analysis
