Parametric and Non Parametric Approach in Structural Equation Modeling (SEM): The Application of Bootstrapping
By Zainudin Awang, Asyraf Afthanorhan, M. Asri, Zainal Abidin Kampus, Gong Badak, Z. Abidin, Kampus Gong Badak. 2015
305 citations recorded by the source corpus.
Lately, there was some attention for the Variance Based SEM (VB-SEM) against that of Covariance Based SEM (CB-SEM) from social science researches regarding the fitness indexes, sample size requirement, and normality assumption. Not many of them aware that VB-SEM is developed based on the non-parametric approach compared to the parametric approach of CB-SEM. In fact the fitness of a model should not be taken lightly since it reflects the behavior of data in relation to the proposed model for the study. Furthermore, the adequacy of sample size and the normality of data are among the main assumptions of parametric test itself. This study intended to clarify the ambiguities among the social science community by employing the data-set which do not meet the fitness requirements and normality assumptions to execute both CB-SEM and VB-SEM. The findings reveal that the result of CB-SEM with bootstrapping is almost similar to that of VB-SEM (bootstrapping as usual). Therefore, the failure to meet the fitness and normality requirements should not be the reason for employing Non-Parametric SEM.
Subfields: Artificial Intelligence, Information Systems and Management, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/b0b232fa48cf6f3be71abb80774c2b995736e1d9
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In Artificial Intelligence
- Theodoros Kyriazos
- Agathi Lakioti
- M. Galanakis
- Joseph F. Hair
- A. Stalikas
- Barry J. Babin
- Nina Krey
- Marko Sarstedt
In Information Systems and Management
- Joseph F. Hair
- Theodoros Kyriazos
- Agathi Lakioti
- Konstantina Prassa
- M. Galanakis
- A. Stalikas
- V. Yotsidi
- Nina Krey
In Management Science and Operations Research
- A. Stalikas
- Theodoros Kyriazos
- Agathi Lakioti
- Konstantina Prassa
- M. Galanakis
- Joseph F. Hair
- V. Yotsidi
- Christian M. Ringle
Citations in the corpus
- Psychometric Evidence of the Brief Resilience Scale (BRS) and Modeling Distinctiveness of Resilience from Depression and Stress (2018, background): “The suggested threshold for AVE is ≥.50 (Fomell & Larcker, 1981; Hair et al., 2010; Awang et al., 2015).”
- Covariance-Based Structural Equation Modeling in the Journal of Advertising: Review and Recommendations (2017, background): “The heavy reliance on maximum likelihood is justified based on the relative robustness of the approach (Awang, Afthanorhan, and Asri 2015; Hox and Bechger 1998).”