Predictive Analytics Using Partial Least Squares Structural Equation Modeling
In recent years, Partial Least Squares Structural Equation Modeling (PLS-SEM) has emerged as a complementary SEM technique to analyze complex relationships among latent variables. Unlike traditional SEM, PLS-SEM is better suited for exploratory research where the goal is to best explain the observed data and/or make predictions about unobserved data (i.e., predictive analytics). Using a model to generate predictions for new observations is both practically useful as well as essential for scientific model development. Predictive power is useful for assessing the relevance of models, comparing competing theories, developing new measures, and more. Using the example of E-Government Citizen Trust models, this talk will introduce how PLS-SEM can be used to compare and select models based on their explanatory and predictive power. The talk is appropriate for anyone who would like to increase their understanding of statistical methods. Researchers and practitioners who are interested in predictive analytics using latent variables will find this talk particularly useful.
Dr. Sharma is Assistant Professor of Information Systems at the Lerner College of Business and Economics, University of Delaware. His research interests include online innovation communities, open source, technology adoption, use, and satisfaction. In addition he is interested in research methods used in business research, particularly Partial Least Squares based SEM. He earned his PhD from University of Pittsburgh.
The Innovative Discoveries Series, sponsored by the Delaware Clinical & Translational Science ACCEL program and the Christiana Care Value Institute, features informal presentations on topics relevant to current research and healthcare practice, led by knowledgeable and experienced presenters. There are offerings for researchers, healthcare providers, and community members of varying levels of experience.
These free talks are held Fridays at noon at Christiana Hospital but can be viewed from your home or office computer. Earn CMEs by participating in-person or online. Lunch is served and all are welcome to attend.
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Contact Sarahfaye Dolman at sarahfaye.f.dolman@christianacare.org with any questions.