Abstract

Foreword - Kenneth A Bollen Preface - Rick H Hoyle The Structural Equation Modeling Approach - Rick H Hoyle Basic Concepts and Fundamental Issues Model Specification - Robert C MacCallum Procedures, Strategies, and Related Issues Estimates and Tests in Structural Equation Modeling - Chih-Ping Chou and Peter M Bentler Structural Equation Models with Nonnormal Variables - Stephen G West, John F Finch and Patrick J Curran Problems and Remedies Evaluating Model Fit - Li-tze Hu and Peter M Bentler Statistical Power in Structural Equation Modeling - David Kaplan Objectivity and Reasoning in Science and Structural Equation Modeling - Stanley A Mulaik and Lawrence R James One Application of Structural Equation Modeling from Two Perspectives - Barbara M Byrne Exploring the EQS and LISREL Strategies Writing about Structural Equation Models - Rick H Hoyle and Abigail T Panter Latent Variable Models for Multitrait-Multimethod Data - Herbert W Marsh and David Grayson Sex-Race Differences in Social Support and Depression in Older Low-Income Adults - Jane A Scott-Lennox and Richard D Lennox Modeling the Relation of Personality Variables to Symptom Complaints - Jay G Hull, Judith C Tedlie and Daniel A Lehn The Unique Role of Negative Affectivity Predictors of Change in Antisocial Behavior during Elementary School for Boys - Mike Stoolmiller, Terry E Duncan and Gerald Patterson

Keywords

Structural equation modelingApplied mathematicsComputer scienceCalculus (dental)Management scienceMathematicsEngineeringStatisticsMedicine

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Publication Info

Year
1996
Type
article
Volume
45
Issue
2
Pages
267-267
Citations
6866
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

6866
OpenAlex
247
Influential
21
CrossRef

Cite This

Murray Smith, Rick H. Hoyle (1996). Structural Equation Modeling: Concepts, Issues, and Applications.. Journal of the Royal Statistical Society Series D (The Statistician) , 45 (2) , 267-267. https://doi.org/10.2307/2988418

Identifiers

DOI
10.2307/2988418

Data Quality

Data completeness: 77%