ABOUT THE WORKSHOP
Partial least squares (PLS) analysis is an alternative to OLS regression, canonical correlation, or structural equation modeling (SEM) of systems of independent and response variables. PLS is sometimes called “variance-based SEM” or “component-based SEM” in contrast to “covariance-based SEM”. PLS is most suitable where the research purpose is a prediction or exploratory modeling. PLS modeling is recommended in an early stage of theoretical development in order to test and validate exploratory models. In this workshop, the SMARTPLS software will be used.
Course content includes:
• Multivariate data structures
• Concepts and indicators
• Measurement and structural models
• Higher order constructs
Model fit assessments
• Path analysis
• Testing mediation effects
• Multi-group analysis
Dr. Karuthan Chinna has a Master Degree in Applied Statistics from the Michigan State University, USA and a PhD in Multivariate Quality Control from the Multimedia University, Malaysia. Dr. Karuthan Chinna has been teaching statistics for 35 years and is also very active in research and consulting. He has published two books; one on Biostatics and the other one on SPSS. He has been a statistical consultant for several projects at the Ministry of Health and other institutions.
UM Student : RM240
UM Staff : RM350
Others : RM500
For further information, please contact us:
Ms. Devi Peramalah / Ms. Ekin
Tel : +603-79673797 Fax : +603-79674975
For further information, kindly email us at firstname.lastname@example.org
Julius Centre University of Malaya (JCUM)
Department of Social & Preventive Medicine, Faculty of Medicine,
University of Malaya, Malaysia.
The Julius Centre University of Malaya (JCUM) was established in 2008. Using advanced epidemiological methods and health data analytics, JCUM aims to be a regional referral centre for learning and research in the areas of epidemiology, clinical epidemiology, evidence-based medicine, and biostatistics. The head of this centre is Assoc Prof Dr Noran Naqiah Mohd Hairi