Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 3 |
Descriptor
| Evaluation Methods | 6 |
| Hypothesis Testing | 6 |
| Structural Equation Models | 6 |
| Correlation | 2 |
| Goodness of Fit | 2 |
| Research Methodology | 2 |
| Association (Psychology) | 1 |
| Biomedicine | 1 |
| Comparative Education | 1 |
| Computer Software | 1 |
| Control Groups | 1 |
| More ▼ | |
Source
| Structural Equation Modeling | 2 |
| Structural Equation Modeling:… | 2 |
| Journal of Educational… | 1 |
| Research in Comparative and… | 1 |
Author
| Davison, Mark L. | 1 |
| Ding, Cody S. | 1 |
| Ferrer, Emilio | 1 |
| Hamagami, Fumiaki | 1 |
| Hau, Kit-Tai | 1 |
| Hoelscher, Michael | 1 |
| Marsh, Herbert W. | 1 |
| McArdle, John J. | 1 |
| Mels, Gerhard | 1 |
| Petersen, Anne C. | 1 |
| Preacher, Kristopher J. | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 6 |
| Reports - Descriptive | 3 |
| Reports - Research | 2 |
| Reports - Evaluative | 1 |
Education Level
| Higher Education | 1 |
Audience
Location
| Australia | 1 |
| Austria | 1 |
| Belgium | 1 |
| Canada | 1 |
| Denmark | 1 |
| Finland | 1 |
| Germany | 1 |
| Ireland | 1 |
| Japan | 1 |
| Netherlands | 1 |
| New Zealand | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkHoelscher, Michael – Research in Comparative and International Education, 2017
This article argues that strong interrelations between methodological and theoretical advances exist. Progress in, especially comparative, methods may have important impacts on theory evaluation. By using the example of the "Varieties of Capitalism" approach and an international comparison of higher education systems, it can be shown…
Descriptors: Higher Education, Comparative Education, Research Methodology, Cross Cultural Studies
Raykov, Tenko; Mels, Gerhard – Structural Equation Modeling: A Multidisciplinary Journal, 2009
A readily implemented procedure is discussed for interval estimation of indexes of interrelationship between items from multiple-component measuring instruments as well as between items and total composite scores. The method is applicable with categorical (ordinal) observed variables, and can be widely used in the process of scale construction,…
Descriptors: Intervals, Structural Equation Models, Biomedicine, Correlation
Preacher, Kristopher J. – Structural Equation Modeling: A Multidisciplinary Journal, 2006
It is often of interest to estimate partial or semipartial correlation coefficients as indexes of the linear association between 2 variables after partialing one or both for the influence of covariates. Squaring these coefficients expresses the proportion of variance in 1 variable explained by the other variable after controlling for covariates.…
Descriptors: Correlation, Hypothesis Testing, Structural Equation Models, Indexes
Ferrer, Emilio; Hamagami, Fumiaki; McArdle, John J. – Structural Equation Modeling, 2004
This article offers different examples of how to fit latent growth curve (LGC) models to longitudinal data using a variety of different software programs (i.e., LISREL, Mx, Mplus, AMOS, SAS). The article shows how the same model can be fitted using both structural equation modeling and multilevel software, with nearly identical results, even in…
Descriptors: Computer Software, Structural Equation Models, Longitudinal Studies, Data Analysis
Ding, Cody S.; Davison, Mark L.; Petersen, Anne C. – Journal of Educational Measurement, 2005
Latent growth curve modeling provides a powerful and flexible tool for researchers to study individual differences in change as well as the correlates and predictors of change. Recent developments in estimation and hypothesis testing procedures are largely based on confirmatory structural equation approaches. In this article, an alternative…
Descriptors: Pattern Recognition, Multidimensional Scaling, Hypothesis Testing, Individual Differences
Marsh, Herbert W.; Hau, Kit-Tai; Wen, Zhonglin – Structural Equation Modeling, 2004
Goodness-of-fit (GOF) indexes provide "rules of thumb"?recommended cutoff values for assessing fit in structural equation modeling. Hu and Bentler (1999) proposed a more rigorous approach to evaluating decision rules based on GOF indexes and, on this basis, proposed new and more stringent cutoff values for many indexes. This article discusses…
Descriptors: Statistical Significance, Structural Equation Models, Evaluation Methods, Evaluation Research
