CRITIQUE OF A PUBLISHED LATENT VARIABLE OR SEM STUDY An Academic presentation by Dr. Nancy Agens, Head, Technical Operations, Statswork Group
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TODAY'S DISCUSSION Outline of Topics
Introduction Structural Equation Modelling Difference Between CB and PLS Example for CB SEM PLS SEM is Better than CB SEM Conclusion
Introductio n Structural equation modelling (SEM) becomes a major statistical technique in examining complex research problems in marketing and international business. The SEM uses covariance based modelling and later few researchers argued to use the partial least square approach for SEM.
Structural Equation Modelling (SEM) Six journals related to the business management and marketing have been considered and the articles related to SEM has been scrutinized for this purpose. After the classification of methods used, it is found that 379 articles used covariance based SEM and 45 used partial least square based SEM. Researchers often interested in finding the same results by using these both methods of Structural equation modelling.
Difference Between CB and PLS Covariance Based (CB)
Partial Least Square (PLS)
The covariance based SEM has a strong theoretical background and it estimates the model by minimizing the covariance matrix of the theoretical model.
The partial least square SEM is a discovery oriented approach, it acts as Predictive Analysis from the latent variable score.
it is used to identify the extent of empirical fit towards the theoretical model.
It is suitable for modelling complex business problems.
Example for CBSEM In covariance based SEM, the complexity of the model influence the goodness-of-fit statistics. For example, consider a chi-square test statistic, then if the complexity of the model or the number of parameters increases then the chi-square value will get decreased. Hence, the result will be either the correct model or the highly fitted model because of the complexity of the problem.
Table: Number of articles used CB and PLS
PLS-SEM is Better than CB-SEM From the results, it is found that only few researchers justified the use of CB-SEM is that to test the theory using statistical hypothesis testing. In the case of PLS-SEM most of the researchers justified the usage of the proposed model for analysis. Thus, it is concluded that the PLS-SEM might be a better choice for conducting an analysis for business and management.
Conclusio n The PLS-SEM is the best methodology than CB-SEM because often the business industry wants a predictive model to enhance their business standard or in investments. If the objective is to develop the Theoretical Framework, then the PLS-SEM is appropriate and the characteristics such as sample size, assumptions of the distribution, the type of measurement should be considered as secondary one. A proper sampling methodology should be adopted for the analysis purpose and sample size and its measurement type is also plays a major role in the inference. However, this may not be the case if you take other field of research.
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