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
Computation | 3 |
Correlation | 2 |
Statistical Analysis | 2 |
Comparative Analysis | 1 |
Computer Software | 1 |
Differences | 1 |
Difficulty Level | 1 |
Error of Measurement | 1 |
Evaluation | 1 |
Factor Analysis | 1 |
Groups | 1 |
More ▼ |
Source
Structural Equation Modeling:… | 3 |
Author
Marcoulides, George A. | 3 |
Raykov, Tenko | 3 |
Publication Type
Journal Articles | 3 |
Reports - Descriptive | 2 |
Reports - Evaluative | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…
Descriptors: Predictive Validity, Reliability, Structural Equation Models, Measures (Individuals)
Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
A directly applicable latent variable modeling procedure for classical item analysis is outlined. The method allows one to point and interval estimate item difficulty, item correlations, and item-total correlations for composites consisting of categorical items. The approach is readily employed in empirical research and as a by-product permits…
Descriptors: Item Analysis, Evaluation, Correlation, Test Items
Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
A latent variable modeling approach for examining population similarities and differences in observed variable relationship and mean indexes in incomplete data sets is discussed. The method is based on the full information maximum likelihood procedure of model fitting and parameter estimation. The procedure can be employed to test group identities…
Descriptors: Models, Comparative Analysis, Groups, Maximum Likelihood Statistics