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Andreas Herrmann

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University of St.Gallen
University of St. Gallen

Course location

University of St.Gallen

Home university

University of St. Gallen
Herrmann-Andreas
Andreas Herrmann is Professor of Marketing and Director of the Institute for Mobility at the University of St.Gallen, Switzerland. He studied Business Administration, Law and Economics, holds a Ph.D. in Marketing from the Koblenz School of Corporate Management, Germany and did his habilitation at the University of Mannheim, Germany. His main research interests are Marketing Management and Behavioral Economics. Andreas Herrmann is author of 15 books and more than 250 journal articles. His recent publication deals with Autonomous Driving (with W. Brenner and R. Stadtler).

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Structural Equation Models

Learning objectives: The course will provide a conceptual introduction to structural equation models, provide a thorough outline of model “fitting” and assessment, show participants: i) how to effectively program structural equation models using available software, ii) how to perform mediation and moderation analysis within the structural equation model framework, iii) how to extend basic models into multiple group situations, iv) and provide an introduction to models where common model assumptions regarding missing and non-normal data are not met. Course content: 1. Introduction to latent variable models, measurement error, path diagrams 2. Mediation models in the structural equation framework 3. Estimation, identification, interpretation of model parameters. 4. Scaling and interpretation issues 5. Scalar programming for structural equation models in R (lavaan). 6. Model fit and model improvement 7. General linear parameter constraints 8. Moderation analysis using multiple-group models. 9. Introduction to models for means and intercepts 10. The FIML approach to analysis with missing data 11. Alternative estimators for non-normal data. 12. Interactions 13. Longitudinal data (as time permits)
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M

2024

Structural Equation Models

Learning objectives: The course will provide a conceptual introduction to structural equation models, provide a thorough outline of model “fitting” and assessment, show participants: i) how to effectively program structural equation models using available software, ii) how to perform mediation and moderation analysis within the structural equation model framework, iii) how to extend basic models into multiple group situations, iv) and provide an introduction to models where common model assumptions regarding missing and non-normal data are not met. Course content: 1. Introduction to latent variable models, measurement error, path diagrams 2. Mediation models in the structural equation framework 3. Estimation, identification, interpretation of model parameters. 4. Scaling and interpretation issues 5. Scalar programming for structural equation models in R (lavaan). 6. Model fit and model improvement 7. General linear parameter constraints 8. Moderation analysis using multiple-group models. 9. Introduction to models for means and intercepts 10. The FIML approach to analysis with missing data 11. Alternative estimators for non-normal data. 12. Interactions 13. Longitudinal data (as time permits)
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