The DOI matches its Crossref record.
Basics of Structural Equation Modeling
Abstract
With the availability of software programs, such as LISREL, EQS, and AMOS, modeling (SEM) techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and test for the plausibility of hypothesizing for a particular data set. Through the use of careful narrative explanation, Maruyama's text describes the logic underlying SEM approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach
Kock, N. (2015) · International Journal of e-Collaboration · doi:10.4018/ijec.2015100101 · Cited by 10,215
Texas A&M International University, Kock, N., Lynn, G., & Stevens Institute of Technology (2012) · Journal of the Association for Information Systems · doi:10.17705/1jais.00302 · Cited by 3,783
Structural Equation Modeling and Natural Systems
Grace, J. B. (2006) · doi:10.1017/cbo9780511617799 · Cited by 2,432
The Impact of Technostress on Role Stress and Productivity
Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007) · Journal of Management Information Systems · doi:10.2753/mis0742-1222240109 · Cited by 1,904
Antonakis, J., Avolio, B. J., & Sivasubramaniam, N. (2003) · The Leadership Quarterly · doi:10.1016/s1048-9843(03)00030-4 · Cited by 1,533
Metadata
- Authors
- Maruyama, G.
- Venue
- Sage eBooks
- Publisher
- SAGE Publications, Inc.
- Published
- 1998
- OpenAlex
- W2163781538
- Cited by
- 1,516
- References
- 0
- FWCI
- 37.52
- Type
- book
- Language
- en
- Open access
- closed
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Basics of Structural Equation Modeling. https://app.cochat.ai/papers/10.4135/9781483345109
- The paper
- Maruyama, G. (1998). Basics of Structural Equation Modeling. Sage eBooks. https://doi.org/10.4135/9781483345109
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
