CRITIQUE OF A PUBLISHED
LATENT VARIABLE OR SEM STUDY
An Academic presentation by
Dr. Nancy Agens, Head, Technical Operations, Statswork
Group www.statswork.com
Email: info@statswork.com
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
Introduction
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 CB-SEM
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 CBSEM
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.
Conclusion
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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