Structural Equation Modelling (SEM)

Authors (Gefen, et al., 2000) believe this approach has many advantages over other methods, for instance Multiple Regression. SEM is also good in terms of path and factor analysis; especially when we are looking for reliability and validity of a research outcome from different angles, which is available through this approach.

 In SEM approach, Partial Least Squares (PLS) method is one of the best. This method has good advantages compared to others, for example LISREL. Whereas sample size is important in SEM, PLS is good for a small sample size research (Gefen et al., 2000) such as our sample, of 300 people. According to Gefen et al. (2000) and Chin (1998), in PLS the minimum sample size need to be 10 times the number of items related to the most complex variable or constructs. “PLS combines a factor analysis with multiple linear regressions to estimate the parameters of the measurement model (item loadings on constructs) together with those of the structural model (regression paths among the constructs) by minimizing residual variance.” (Gefen and Straub, 2004).

With the help of PLS we are able to test

-          validity of discriminant

-          convergent scales

We have private courses in PLS. However, if you do not have time to attend this course, you can have some private sessions with me or alternatively, you can order your project and we will do that for you.