Partial Least Square (PLS)

Partial Least Square (PLS) PLS path modeling is commonly used in business and social sciences with the purpose of predicting endogenous latent variables as well as estimating and examining the relationships between these latent variables (causal analysis).

Compared to the covariance-based structural equation modeling techniques, PLS is a vigorous technique with usually less restraining distributional requirements and assumptions. Additionally, PLS-PM allows constructs to be formatively and more willingly measured.

There are no specific prerequisites for this course though some knowledge of statistics is presumed. Furthermore, having some knowledge of linear regression techniques will also be beneficial for the participants.

The main objectives of this course are:

 (1) to provide detailed methodological introduction into the PLS path modeling approach (particularly, the nature of causal modeling, analytical objectives, some statistics)

 (2) the assessment of measurement results, and

 (3) complementary analytical techniques. An essential part of this course is the practical applications and the use of a PLS software application.

This course is perfect for you if you are doing your research based on Structural Equation Modelling (SEM).

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.