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
Antisocial Behavior | 3 |
Structural Equation Models | 3 |
Computer Software | 2 |
Evaluation Methods | 2 |
Measurement Techniques | 2 |
Regression (Statistics) | 2 |
Adolescents | 1 |
Adults | 1 |
Aggression | 1 |
Behavior Problems | 1 |
Children | 1 |
More ▼ |
Source
Structural Equation Modeling:… | 3 |
Author
Asparouhov, Tihomir | 1 |
Blozis, Shelley A. | 1 |
Cho, Young Il | 1 |
Dekovic, Maja | 1 |
Hoijtink, Herbert | 1 |
Muthen, Bengt | 1 |
van de Schoot, Rens | 1 |
Publication Type
Journal Articles | 3 |
Reports - Evaluative | 2 |
Reports - Descriptive | 1 |
Education Level
Elementary Education | 1 |
Grade 3 | 1 |
Audience
Location
Netherlands | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
van de Schoot, Rens; Hoijtink, Herbert; Dekovic, Maja – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Researchers often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model. It is currently not possible to test these so-called informative hypotheses in structural equation modeling software. We offer a solution to this problem using M"plus." The hypotheses are…
Descriptors: Structural Equation Models, Computer Software, Hypothesis Testing, Statistical Analysis
Blozis, Shelley A.; Cho, Young Il – Structural Equation Modeling: A Multidisciplinary Journal, 2008
The coding of time in latent curve models has been shown to have important implications in the interpretation of growth parameters. Centering time is often done to improve interpretation but may have consequences for estimated parameters. This article studies the effects of coding and centering time when there is interindividual heterogeneity in…
Descriptors: Test Items, Coding, Time, Longitudinal Studies
Asparouhov, Tihomir; Muthen, Bengt – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made…
Descriptors: Structural Equation Models, Testing, Factor Analysis, Research Methodology