scholarly journals Exploratory Structural Equation Modeling: Practical Guidelines and Tutorial With a Convenient Online Tool for Mplus

2022 ◽  
Vol 12 ◽  
Author(s):  
Llewellyn E. van Zyl ◽  
Peter M. ten Klooster
Keyword(s):  
Mental Health ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Public Perception ◽  
Equation Modeling ◽  
Exploratory Structural Equation Modeling ◽  
Promising Alternative ◽  
Online Tool ◽  
Confirmatory Factor ◽  
Analytical Approaches

Critics of positive psychology have questioned the validity of positive psychological assessment measures (PPAMs), which negatively affects the credibility and public perception of the discipline. Psychometric evaluations of PPAMs have shown that various instruments produce inconsistent factor structures between groups/contexts/times frames, that their predictive validity is questionable, and that popular PPAMs are culturally biased. Further, it would seem positive psychological researchers prioritize date-model-fit over measurement quality. To address these analytical challenges, more innovative and robust approaches toward the validation and evaluation of PPAMs are required to enhance the discipline's credibility and to advance positive psychological science. Exploratory Structural Equation Modeling (ESEM) has recently emerged as a promising alternative to overcome some of these challenges by incorporating the best elements from exploratory- and confirmatory factor analyses. ESEM is still a relatively novel approach, and estimating these models in statistical software packages can be complex and tedious. Therefore, the purpose of this paper is to provide novice researchers with a practical tutorial on how to estimate ESEM with a convenient online tool for Mplus. Specifically, we aim to demonstrate the use of ESEM through an illustrative example by using a popular positive psychological instrument: the Mental Health Continuum-SF. By using the MHC-SF as an example, we aim to provide (a) a brief overview of ESEM (and different ESEM models/approaches), (b) guidelines for novice researchers on how to estimate, compare, report, and interpret ESEM, and (c) a step-by-step tutorial on how to run ESEM analyses in Mplus with the De Beer and Van Zy ESEM syntax generator. The results of this study highlight the value of ESEM, over and above that of traditional confirmatory factor analytical approaches. The results also have practical implications for measuring mental health with the MHC-SF, illustrating that a bifactor ESEM Model fits the data significantly better than any other theoretical model.

scholarly journals Assessing the Unidimensionality of Clayton’s Environmental Identity Scale Using Confirmatory Factor Analysis (CFA) and Bifactor Exploratory Structural Equation Modeling (bifactor-ESEM)

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Paulo Moreira ◽  
Ana Loureiro ◽  
Richard Inman ◽  
Pablo Olivos-Jara
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Bifactor Model ◽  
Equation Modeling ◽  
Environmental Identity ◽  
Order Model ◽  
Exploratory Structural Equation Modeling ◽  
Confirmatory Factor

A relevant intrapersonal characteristic for understanding intentions and behavior toward environmental sustainability is the degree to which nature is important for a person’s self-definition. Clayton’s Environmental Identity (EID) scale purports to measure this construct. However, a limited number of prior exploratory studies of this measure have supported different factor structures. Hence, our initial aim was to develop an understanding of the dimensionality of Clayton’s 24-item EID scale by testing competing latent structures using confirmatory factor analysis. We analyzed self-reported data from 458 adults (Mage = 26.7 years; 81% female). Four a priori models (a first-order model, a second-order model, a unidimensional model, and a bifactor model) did not show satisfactory fit to the data. An ancillary analysis using bifactor exploratory structural equation modeling (bifactor-ESEM) indicated a bifactor model with three specific factors had a good fit to the data. The factor loadings of this model and values for bifactor indices (Omega Hierarchical and Explained Common Variance [ECV]) indicated a single mean score across all EID scale items taps into an essentially unidimensional construct and is therefore appropriate to interpret. In sum, our study provides a critical insight into the dimensionality of Clayton’s EID scale that will be valuable when applying this measure for research and intervention purposes.

Evaluating the construct validity of Stress Overload Scale-Short using exploratory structural equation modeling

2017 ◽  
Vol 25 (7) ◽  
pp. 913-921 ◽  
Author(s):  
Wenlong Mu ◽  
Wenjie Duan
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Negative Emotion ◽  
Equation Modeling ◽  
Exploratory Structural Equation Modeling ◽  
Confirmatory Factor ◽  
Personal Vulnerability ◽  
Negative Emotion Symptoms

This study used exploratory structural equation modeling and confirmatory factor analysis to examine the construct validity of the Chinese version of Stress Overload Scale-Short, which included personal vulnerability and event load. The participants included 629 community residents and 495 university students. The results indicated a better goodness-of-fit using exploratory structural equation modeling compared with confirmatory factor analysis. The Stress Overload Scale-Short performed well in distinguishing individuals with more negative emotion symptoms from the general population. A moderation analysis demonstrated that social support moderates the effect of personal vulnerability on negative emotion symptoms. These results facilitated the application of Stress Overload Scale-Short in the current population.

scholarly journals Psychometric Properties of the Chinese Bermond–Vorst Alexithymia Questionnaire: An Exploratory Structural Equation Modeling Study

2021 ◽  
Vol 15 ◽  
pp. 183449092199142
Author(s):  
Zhihao Wang ◽  
Ting Wang ◽  
Katharina S. Goerlich ◽  
Riddhi J. Pitliya ◽  
Bob Bermond ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Psychometric Properties ◽  
Structural Equation ◽  
Equation Modeling ◽  
Exploratory Structural Equation Modeling ◽  
Affective Factors ◽  
Confirmatory Factor ◽  
Affective Components ◽  
Acceptable Reliability ◽  
Tas 20

The Toronto Alexithymia Scale-20 (TAS-20) has been widely used to assess alexithymia. The Bermond–Vorst Alexithymia Questionnaire (BVAQ) assesses two additional features of alexithymia—the affective factors of emotionalizing and fantasizing, which are not included in the TAS-20. However, there is currently no Chinese version of the BVAQ. Here, the authors collected data from 439 college students (293 females, aged 17–27, mean ± SD = 20.25 ± 1.88) to evaluate the psychometric properties for a Chinese BVAQ translation. Exploratory structural equation modeling and confirmatory factor analysis provided satisfactory validity and acceptable reliability for a six-factor first-order solution of a 35-item Chinese BVAQ. This adaptation retained the five original BVAQ factors (identifying, analyzing, verbalizing, emotionalizing, and fantasizing) and further specified the factor of identifying (successful identifying and unsuccessful identifying feelings). The authors also found a two-factor second-order model of cognitive and affective components for alexithymia in the Chinese population. Higher correlations with the TAS-20 were observed for identifying, analyzing, and verbalizing feelings (0.34 ∼ 0.61) relative to fantasizing and emotionalizing (0.02 ∼ −0.05). These results support the construct validity of the adaptation. This work provides a reliable and valid Chinese adaptation of the BVAQ.

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