SMARTPLS 4 workshop (Part 2): 

Learning data analysis for PLS-SEM, CB-SEM, PROCESS and REGRESSION using SMARTPLS 4

Date: 14 - 15 December 2024 (Saturday - Sunday) / Time: 9 - 4 pm

Dear All,

You are cordially invited to join the following workshop: 

Workshop Title: SMARTPLS 4 workshop (Part 2): 

Learning data analysis for PLS-SEM, CB-SEM, PROCESS and REGRESSION using SMARTPLS 4

Speaker: Professor Dr Chua Yan Piaw

Date: 14 - 15 December 2024 (Saturday - Sunday) 

Time: 9.00 am - 4.00 pm

Method: Online (Googlemeet)

Fee: RM200

Certificate: Provided

Registration: Ms. Lina (email: researchtreeresources@gmail.com) 

SMARTPLS 4 is a powerful and user-friendly Structural Equation Modeling analysis software used in research for establishing validity and reliability of research instruments, examining causal relationships between multiple independent and dependent variables with multiple indicators, as well as evaluating the predictive power of research models.

The latest version of SMARTPLS 4 includes four methods of data analysis, i.e., (1) PLS-SEM, (2) CB-SEM, (3) PROCESS and (4) REGRESSION. The PLS-SEM is a non-parametric SEM analysis method while the CB-SEM is a parametric SEM analysis method. The PROCESS method is used especially in analyzing moderated mediation model by controlling selected covariates, while the REGRESSION method is used for necessary condition analysis, multiple logistics regression analysis and multiple linear regression analysis.

This 2-day workshop is for postgraduate students, academicians, and researchers with no / little basic working knowledge of statistics and SEM, who are/will be required to carry out statistical analysis for their research.

Through the workshop, participants will learn the basic methods of drawing PLS-SEM, CB-SEM, PROCESS and REGRESSION models in SMARTPLS 4, analyzing and reporting the results. This would assist the participants in planning, conducting, analyzing and reporting findings of their own research and for publications.

1.  Introduction to SMARTPLS 4 – The four data analysis methods

2.  The PLS-SEM method

a. Drawing PLS-SEM models

b. Construct validity, construct reliability, discriminant validity and collinearity

c. Predictive power of the model

d. IPMA analysis

e. Model fit

f. Reporting the results of the analysis

3.  The CB-SEM method

a. Analyzing normality of data

b. Drawing CB-SEM models and analyzing the models for construct validity, construct reliability and discriminant validity

c. Causal relationships and correlations between variables

d. Model fit and model modifications

e. Reporting the results of the analysis

4.  The PROCESS method

a. Drawing PROCESS model

b. Moderated mediation models

c. Controlling covariates in the PROCESS

d. Reporting the results of CB-SEM analysis

5. The REGRESSION method

a. Necessary condition analysis - NCA charts, Bottleneck table  

b. Multiple logistic regression analysis – Odds ratio, predictive power

c. Reporting the results of CB-SEM analysis