Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming
Abstract
This book illustrates the ease with which AMOS 4.0 can be used to address research questions that lend themselves to structural equation modeling (SEM). This goal is achieved by: 1) presenting a nonmathematical introduction to the basic concepts and applications of structural equation modeling; 2) demonstrating basic applications of SEM using AMOS 4.0; and 3) highlighting features of AMOS 4.0 that address important caveats related to SEM analyses. Written in a "user-friendly" style, the author "walks" the reader through 10 SEM applications from model specification to estimation to the assessment and interpretation of the output. Each of the book's applications is accompanied by: a statement of the hypothesis being tested; a schematic representation of the model under study; the use and function of a wide variety of icons and pull-down menus; a full explanation of related AMOS Graphic input models and output files; a model input file based on AMOS BASIC; and the published reference from which each application was drawn.
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Cites
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
The measurement model of the GenAI-LLs demonstrates a satisfactory model fit.
“The findings revealed that the measurement model demonstrates a satisfactory model fit.”
From Development and validation of the Generative AI Literacy for Learning Scale (GenAI-LLs) (2025) · cites this paper as Byrne, 2013
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Cited by 1,156
- Authors
- Byrne, B. M.
- Corresponding author
- Byrne, Barbara M.
- Venue
- Psychology Press eBooks
- Publisher
- Psychology Press
- Published
- 2013-05-24
- OpenAlex
- W4301281022
- Cited by
- 1,156
- References
- 0
- Citations by year
- 2026: 40 · 2025: 75 · 2024: 90 · 2023: 93 · 2022: 128 · 2021: 134 · 2020: 99 · 2019: 71 · 2018: 68 · 2017: 51 · 2016: 58 · 2015: 46 · 2014: 28 · 2013: 27 · 2012: 34
- FWCI
- 16.63
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Psychology Press eBooks (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- structural equation modeling, model specification, model estimation, hypothesis testing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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