Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 2 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 4 |
Descriptor
| Data Analysis | 6 |
| Statistical Distributions | 6 |
| Structural Equation Models | 6 |
| Computation | 3 |
| Social Science Research | 3 |
| Error of Measurement | 2 |
| Evaluation Methods | 2 |
| Mathematical Formulas | 2 |
| Maximum Likelihood Statistics | 2 |
| Meta Analysis | 2 |
| Scaling | 2 |
| More ▼ | |
Source
| Structural Equation Modeling:… | 2 |
| Grantee Submission | 1 |
| International Journal of… | 1 |
| Measurement:… | 1 |
| Psychometrika | 1 |
Author
| Ke-Hai Yuan | 2 |
| Ling Ling | 2 |
| Zhiyong Zhang | 2 |
| Bentler, Peter M. | 1 |
| Byrne, Barbara M. | 1 |
| Chan, Wai | 1 |
| Cohen, Allan S. | 1 |
| Kim, Seohyun | 1 |
| Lu, Zhenqiu | 1 |
| Raykov, Tenko | 1 |
| Yuan, Ke-Hai | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 6 |
| Reports - Descriptive | 3 |
| Reports - Research | 3 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Grantee Submission, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
Ke-Hai Yuan; Ling Ling; Zhiyong Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Data in social and behavioral sciences typically contain measurement errors and do not have predefined metrics. Structural equation modeling (SEM) is widely used for the analysis of such data, where the scales of the manifest and latent variables are often subjective. This article studies how the model, parameter estimates, their standard errors…
Descriptors: Structural Equation Models, Computation, Social Science Research, Error of Measurement
Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S. – Measurement: Interdisciplinary Research and Perspectives, 2018
Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…
Descriptors: Bayesian Statistics, Structural Equation Models, Computation, Social Science Research
Raykov, Tenko – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article is concerned with the question of whether the missing data mechanism routinely referred to as missing completely at random (MCAR) is statistically examinable via a test for lack of distributional differences between groups with observed and missing data, and related consequences. A discussion is initially provided, from a formal logic…
Descriptors: Data Analysis, Statistical Analysis, Probability, Structural Equation Models
Peer reviewedByrne, Barbara M. – International Journal of Testing, 2001
Uses a confirmatory factor analytic (CFA) model as a paradigmatic basis for the comparison of three widely used structural equation modeling computer programs: (1) AMOS 4.0; (2) EQS 6; and (3) LISREL 8. Comparisons focus on aspects of programs that bear on the specification and testing of CFA models and the treatment of incomplete, nonnormally…
Descriptors: Comparative Analysis, Computer Software, Data Analysis, Statistical Distributions
Yuan, Ke-Hai; Bentler, Peter M.; Chan, Wai – Psychometrika, 2004
Data in social and behavioral sciences typically possess heavy tails. Structural equation modeling is commonly used in analyzing interrelations among variables of such data. Classical methods for structural equation modeling fit a proposed model to the sample covariance matrix, which can lead to very inefficient parameter estimates. By fitting a…
Descriptors: Structural Equation Models, Statistical Distributions, Evaluation Methods, Data Analysis

Direct link
