Statistical Data Analysis Services

Structural equation modeling  (SEM) becomes a major statistical technique in examining complex research problems in marketing and  international business . In most research, the SEM uses covariance-based modelling and later few researchers argued to use the partial least square approach for SEM. In this blog, a critical review of the SEM technique presented in Richter et al (2014) is discussed with application to the business sector. SEM Study (SEM Using AMOS) Six journals related to  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 are often interested in finding the same results by using these both methods of Structural equation modelling. However, the consistency of the partial least square method or the development of a n...

SEM using AMOS Structural Equation Modelling (SEM) is a widely used technique in statistics to primarily study relationships based on structures. It encompasses various models involving mathematics, statistical procedures etc. This technique is known to be extremely effective when it comes to measuring latent constructs. Many of us might be familiar with concepts like Multiple Regression Analysis and Factor Analysis , this in simple term, is a combination of these techniques. It is, in fact, a mere extension of the General Linear Model. You can test a bunch of regression techniques at the same time. Structural Equation Modelling includes a model that makes room for a lot of other statistical techniques such as path analysis, confirmatory factor analysis and latent growth modelling etc. This is impressive as SEM as a type of model covers many models that are both traditional and complex. It is also effective in the assessment of variance and Multiple Regression along with e...