2017
DOI: 10.4236/psych.2017.89086
|View full text |Cite
|
Sign up to set email alerts
|

Best Practice Recommendations for Using Structural Equation Modelling in Psychological Research

Abstract: Although structural equation modelling (SEM) is a popular analytic technique in the social sciences, it remains subject to misuse. The purposes of this paper are to assist psychologists interested in using SEM by: 1) providing a brief overview of this method; and 2) describing best practice recommendations for testing models and reporting findings. We also outline several resources that psychologists with limited familiarity about SEM may find helpful.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

4
52
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
9
1

Relationship

0
10

Authors

Journals

citations
Cited by 67 publications
(62 citation statements)
references
References 28 publications
(26 reference statements)
4
52
0
Order By: Relevance
“…In both the measurement- and structural models, perceived health and perceived financial situation was controlled for by regressing such on perceived employability and intention to work until one’s retirement age. The results were reported in line with the best practice guidelines for SEM by Morrison et al (2017).…”
Section: Methodssupporting
confidence: 85%
“…In both the measurement- and structural models, perceived health and perceived financial situation was controlled for by regressing such on perceived employability and intention to work until one’s retirement age. The results were reported in line with the best practice guidelines for SEM by Morrison et al (2017).…”
Section: Methodssupporting
confidence: 85%
“…Optimal fit indicators were sought and therefore items demonstrating poor loadings (<0.3) were removed. Second, a structural analysis, was used to determine the nature of the direct, and indirect effects of organizational support on volunteer mental health outcomes (Morrison, Morrison, & McCutcheon, 2017). Data analyses were carried out using SPSS (Version 25) and Mplus (Version 7.4: Muthén & Muthén, 1998.…”
Section: Discussionmentioning
confidence: 99%
“…This objective was addressed by using a structural equation model (SEM) approach. SEM is a statistical technique that combines factor analysis and multiple regression allowing to examine and test the hypothesized simultaneous covariation among latent variables (Morrison et al, 2017; Schreiber et al, 2006). In other words, SEM enables researchers to inspect whether the interrelations among objectively measured variables, clustered in latent variables by their shared variance, behave like in a given specific theoretical model.…”
Section: Introductionmentioning
confidence: 99%