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) | 4 |
Descriptor
Computation | 4 |
Error Patterns | 4 |
Models | 3 |
Evaluation Methods | 2 |
Factor Analysis | 2 |
Monte Carlo Methods | 2 |
Simulation | 2 |
Assignments | 1 |
Behavioral Science Research | 1 |
Classification | 1 |
Comparative Analysis | 1 |
More ▼ |
Source
Educational and Psychological… | 4 |
Author
Harring, Jeffrey R. | 1 |
Holden, Jocelyn E. | 1 |
Kelley, Ken | 1 |
Kiers, Henk A. L. | 1 |
Li, Ming | 1 |
Stuive, Ilse | 1 |
Timmerman, Marieke E. | 1 |
Weiss, Brandi A. | 1 |
Yoo, Jin Eun | 1 |
ten Berge, Jos M. F. | 1 |
Publication Type
Journal Articles | 4 |
Reports - Research | 3 |
Reports - Evaluative | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Harring, Jeffrey R.; Weiss, Brandi A.; Li, Ming – Educational and Psychological Measurement, 2015
Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…
Descriptors: Structural Equation Models, Statistical Analysis, Monte Carlo Methods, Computation
Holden, Jocelyn E.; Kelley, Ken – Educational and Psychological Measurement, 2010
Classification procedures are common and useful in behavioral, educational, social, and managerial research. Supervised classification techniques such as discriminant function analysis assume training data are perfectly classified when estimating parameters or classifying. In contrast, unsupervised classification techniques such as finite mixture…
Descriptors: Discriminant Analysis, Classification, Computation, Behavioral Science Research
Stuive, Ilse; Kiers, Henk A. L.; Timmerman, Marieke E.; ten Berge, Jos M. F. – Educational and Psychological Measurement, 2008
This study compares two confirmatory factor analysis methods on their ability to verify whether correct assignments of items to subtests are supported by the data. The confirmatory common factor (CCF) method is used most often and defines nonzero loadings so that they correspond to the assignment of items to subtests. Another method is the oblique…
Descriptors: Assignments, Simulation, Construct Validity, Factor Analysis
Yoo, Jin Eun – Educational and Psychological Measurement, 2009
This Monte Carlo study investigates the beneficiary effect of including auxiliary variables during estimation of confirmatory factor analysis models with multiple imputation. Specifically, it examines the influence of sample size, missing rates, missingness mechanism combinations, missingness types (linear or convex), and the absence or presence…
Descriptors: Monte Carlo Methods, Research Methodology, Test Validity, Factor Analysis