Cited by 237Psychometric Methodologies and TestingAdvanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

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Causation issues in structural equation modeling research

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Bullock, Heather E., Harlow, Lisa L., Mulaik, Stanley A.·1994·Structural Equation Modeling: A Multidisciplinary Journal

DOI 10.1080/10705519409539977

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Abstract

As the use of structural equation modeling (SEM) has increased, confusion has grown concerning the correct use of and the conclusions that can be legitimately drawn from these methodologies. It appears that much of the controversy surrounding SEM is related to the degree of certainty with which causal statements can be drawn from these procedures. SEM is discussed in relation to the conditions necessary for providing causal evidence. Both the weaknesses and the strengths of SEM are examined. Although structural modeling cannot ensure that necessary causal conditions have been met, it is argued that SEM methods may offer the potential for tentative causal inferences to be drawn when used with carefully specified and controlled designs. Keeping in mind that no statistical methodology can in and of itself determine causality, specific guidelines are suggested to help researchers approach a potential for providing causal evidence with SEM procedures.

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Authors: Bullock, H. E., Harlow, L. L., & Mulaik, S. A.
Affiliations: University of Rhode Island (US)
Georgia Institute of Technology (US)
ORCID: Harlow, Lisa L.
Venue: Structural Equation Modeling: A Multidisciplinary Journal
Publisher: Informa UK Limited
Published: 1994-01
Volume: 1
Issue: 3
Pages: 253-267
ISSN: 1070-5511 (ISSN-L)
1532-8007
DOI: 10.1080/10705519409539977
OpenAlex: W2000776953
Cited by: 237
References: 70
Citations by year: 2026: 6 · 2025: 9 · 2024: 6 · 2023: 12 · 2022: 14 · 2021: 18 · 2020: 20 · 2019: 7 · 2018: 11 · 2017: 11 · 2016: 10 · 2015: 6 · 2014: 11 · 2013: 8 · 2012: 10
FWCI: 6.20
Type: journal article
Language: en
Open access: green
digitalcommons.uri.edu
Licence: cc-by
Locations: Structural Equation Modeling A Multidisciplinary Journal (publishedVersion)
Journal of Media Literacy Education (submittedVersion, cc-by)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: structural equation modeling, causality, causal inference, causal evidence, research design, methodological limitations, research guidelines

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Causation issues in structural equation modeling research

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