Testing Interaction Effects in LISREL: Examination and Illustration of Available Procedures

Cortina, Jose M.; Chen, Gilad; Dunlap, William P.

doi:10.1177/109442810144002

Cited by 512Psychometric Methodologies and TestingStatistical Methods and ApplicationsStatistical Methods and Bayesian Inference

Testing Interaction Effects in LISREL: Examination and Illustration of Available Procedures

Cortina, Jose M., Chen, Gilad, Dunlap, William P.·2001·Organizational Research Methods

DOI 10.1177/109442810144002

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Abstract

The concomitant proliferation of causal modeling and hypotheses of multiplicative effects has brought about a tremendous need for procedures that allow the testing of moderated structural equation models (MSEMs). The seminal work of Kenny and Judd and Hayduk has been drawn on by several authors in the past 10 years, thus producing procedures that allow for such tests. Yet, utilization of MSEMs in empirical research has been quite rare. The purposes of this article are twofold. First, the authors discuss general issues with respect to multivariate normality, indicators of latent products, the nature of latent products, and identification problems in MSEM. Second, they review and illustrate techniques that are available for the testing of interaction effects in structural equation models.

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Asymptotic distribution-free estimators require much larger sample sizes (in the 1,000s) than were available in this study.
“Asymptotic distribution-free estimators are now available for non-normal data (Browne, 1984;Jo ¨reskog & So ¨rbom, 2004) but they require much larger sample sizes (in the 1,000 s; see Cortina, Chen & Dunlap, 2001;Hu, Bentler, & Kano, 1992) than was available here.”
From Confirmatory Factor Analysis of the Behavior Rating Inventory of Executive Function-Adult Version in Healthy Adults and Application to Attention-Deficit/Hyperactivity Disorder (2013) · cites this paper as Cortina, Chen & Dunlap, 2001
The study used normal theory maximum likelihood estimators that have been shown to be robust to at least modest violations of multivariate normality.
“Rather, we used normal theory maximum likelihood estimators that have been shown to be robust to at least modest violations of the multivariate normality assumption (Chou, Bentler, & Satorra, 1991;Cortina et al., 2001).”
From Confirmatory Factor Analysis of the Behavior Rating Inventory of Executive Function-Adult Version in Healthy Adults and Application to Attention-Deficit/Hyperactivity Disorder (2013) · cites this paper as Cortina et al., 2001

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Authors: Cortina, J. M., Chen, G., & Dunlap, W. P.
Affiliations: George Mason University (US)
Tulane University (US)
Venue: Organizational Research Methods
Publisher: SAGE Publications
Published: 2001-10
Volume: 4
Issue: 4
Pages: 324-360
ISSN: 1094-4281 (ISSN-L)
1552-7425
DOI: 10.1177/109442810144002
OpenAlex: W2146073395
Cited by: 512
References: 30
Citations by year: 2026: 20 · 2025: 10 · 2024: 21 · 2023: 15 · 2022: 23 · 2021: 20 · 2020: 31 · 2019: 27 · 2018: 29 · 2017: 28 · 2016: 23 · 2015: 38 · 2014: 35 · 2013: 33 · 2012: 27
FWCI: 5.69
Type: journal article
Language: en
Open access: closed
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Organizational Research Methods (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: interaction effects, multivariate normality, identification problem, LISREL, multiplicative effects, latent variable interactions

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Testing Interaction Effects in LISREL: Examination and Illustration of Available Procedures

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