Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 1 |
Descriptor
| Matrices | 3 |
| Statistical Analysis | 3 |
| Goodness of Fit | 2 |
| Research Design | 2 |
| Analysis of Variance | 1 |
| Comparative Analysis | 1 |
| Data Analysis | 1 |
| Factor Analysis | 1 |
| Item Response Theory | 1 |
| Item Sampling | 1 |
| Mathematical Models | 1 |
| More ▼ | |
Source
| Journal of Educational… | 3 |
Author
| Algina, James | 1 |
| Kuhn, Jorg-Tobias | 1 |
| Lomax, Richard G. | 1 |
| Ranger, Jochen | 1 |
| Sirotnik, Kenneth | 1 |
| Wellington, Roger | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Ranger, Jochen; Kuhn, Jorg-Tobias – Journal of Educational Measurement, 2012
The information matrix can equivalently be determined via the expectation of the Hessian matrix or the expectation of the outer product of the score vector. The identity of these two matrices, however, is only valid in case of a correctly specified model. Therefore, differences between the two versions of the observed information matrix indicate…
Descriptors: Goodness of Fit, Item Response Theory, Models, Matrices
Peer reviewedLomax, Richard G.; Algina, James – Journal of Educational Measurement, 1979
Results of using multimethod factor analysis and exploratory factor analysis for the analysis of three multitrait-multimethod matrices are compared. Results suggest that the two methods can give quite different impressions of discriminant validity. In the examples considered, the former procedure tends to support discrimination while the latter…
Descriptors: Comparative Analysis, Factor Analysis, Goodness of Fit, Matrices
Peer reviewedSirotnik, Kenneth; Wellington, Roger – Journal of Educational Measurement, 1977
A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)
Descriptors: Analysis of Variance, Data Analysis, Item Sampling, Mathematical Models

Direct link
