A Brief Guide to Structural Equation Modeling
Bibliographic Data
| ID | 8913484 |
|---|---|
| Authors | Rebecca Weston (0000-0003-0457-1970, Southern Illinois University,, corresponding author), Paul A Gore (ACT, Inc.) |
| Year | 2006 |
| Volume | 34 |
| Issue | 5 |
| Pages | 719-751 |
| Publication date | 2006-08-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Counseling Psychologist (JOURNAL) |
| Journal identifiers | ISSN: 0011-0000 • E-ISSN: 1552-3861 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/0011000006286345 |
| OpenAlex | W2109223853 |
| Language | EN |
| Citations received | 661 |
| References cited | 51 |
To complement recent articles in this journal on structural equation modeling (SEM) practice and principles by Martens and by Quintana and Maxwell, respectively, the authors offer a consumer’s guide to SEM. Using an example derived from theory and research on vocational psychology, the authors outline six steps in SEM: model specification, identification, data preparation and screening, estimation, evaluation of fit, and modification. In addition, the authors summarize the debates surrounding some aspects of SEM (e.g., acceptable sample size, fit indices), with recommendations for application. They also discuss the need for considering and testing alternative models and present an example, with details on determining whether alternative models result in a significant improvement in fit to the observed data
Causal model · Complement (music · Identification (biology · Machine learning · Management science · Sample (material · Sample size determination · Statistics · Structural equation modeling · Behavioral Health and Interventions · Computer Science · Engineering · Job Satisfaction and Organizational Behavior · Mathematics · Psychology · Psychometric Methodologies and Testing
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A Beginner's Guide to Structural Equation Modeling
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Analyzing data from experimental studies
Missing Data Techniques for Structural Equation Modeling.
Applications of Structural Equation Modeling in Psychological Research
The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis
Reporting Analyses of Covariance Structures
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Inference and missing data
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Fit indices in covariance structure modeling
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Principles and practice in reporting structural equation analyses.
Power analysis and determination of sample size for covariance structure modeling.
Testing Structural Equation Models
Model Modification in Covariance Structure Modeling
A Monte Carlo Investigation of Methods for Controlling Type I Errors with Specification Searches in Structural Equation Modeling
Structural Model Evaluation and Modification
Structural equation modeling in practice
A New Incremental Fit Index for General Structural Equation Models
The Use of Structural Equation Modeling in Counseling Psychology Research
The Counseling Psychologist, 1969-1988
Effect-Size Measures and Meta-Analytic Thinking in Counseling Psychology Research
Factor Analysis in Counseling Psychology Research, Training, and Practice
Implications of Recent Developments in Structural Equation Modeling for Counseling Psychology
Guidelines for Meta-Analyses of Counseling Psychology Research
Discriminant Analysis in Counseling Psychology Research
Advanced Applications of Structural Equation Modeling in Counseling Psychology Research
Treating Cronbach’s Alpha Reliability Coefficients as Data in Counseling Research
The moderator–mediator variable distinction in social psychological research
Comparative fit indexes in structural models
The moderator-mediator variable distinction in social psychological research
Principles and Practice of Structural Equation Modeling
Alternative Ways of Assessing Model Fit
| Unique citing works | 661 |
|---|---|
| Citations per year | 33,05 |
| Citation span | 2006 - 2026 (21) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 655 |