18 May - 19 May
May 18 to May 19, 2021

COURSE: FOUNDATIONS OF PLS-SEM USING SMARTPLS

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This two-day course introduces participants to the state-of-the-art of partial least squares structural equation modeling (PLS-SEM) using the world-leading PLS-SEM software SmartPLS.

The first day of the course provides a profound introduction to PLS-SEM. Participants will learn the foundations of PLS-SEM and how to apply it by means of the SmartPLS 3 software. The second day will cover the appropriate evaluation of the measurement and structural model including recent developments in model evaluation. The instructors will make use of several examples and hands-on exercises using the SmartPLS 3 software. 

PLS-SEM is a composite-based approach to SEM, which aims at maximizing the explained variance of dependent constructs in the path model. Compared to other SEM techniques, PLS-SEM allows researchers to estimate very complex models with many constructs and indicator variables. Furthermore, PLS-SEM allows to estimate reflective and formative constructs and generally offers much flexibility in terms of data requirements.

Learning Outcomes

This course has been designed to familiarize participants with the potentials of using the multivariate analysis method PLS-SEM in their research. The objectives of this course are to provide (1) an in-depth methodological introduction into the PLS-SEM approach (the nature of causal modeling, analytical objectives, some statistics), (2) the evaluation of measurement results, and (3) the evaluation of the structural model results. More specifically, participants will understand the following topics:

  • Model development and fundamentals of PLS-SEM and latent variable models
  • PLS path model estimation including the weighted PLS (WPLS) and consistent PLS (PLSc)
  • Assessment and reporting of measurement and structural model results including Bootstrapping
  • Prediction-oriented results analysis including PLSpredict
  • New criteria for model assessment such as HTMT for discriminant validity, goodness of fit (e.g., SRMR), and model comparison & model selection

Instructors:

Prof. Dr. Christian Ringle 
Prof. Marko Sarstedt
Dr. Jan-Michael Becker

This course has been designed for full-time faculty and PhD students who are interested in learning how to use the PLS-SEM method in their own research applications. Basic knowledge of multivariate statistics and SEM techniques is helpful, but not required.

Participants will receive a certificate of attendance. Universities and academic institutions usually acknowledge this course with a workload of 6 ECTS.

XING-Events 


Date:
May 18 to May 19, 2021
Time:
9 am - 5 pm


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