Agenda
Introduction to Structural Equation Modeling
Equivalent models - Steps in performing SEM analysis: Model specification, Estimation of free parameters, Assessment of model and model fit, Model modification, Sample size and power, Interpretation and communication - Advanced uses - SEM-specific software
Path Analysis
Causality - Latent variable model - Path modeling - Path coefficient - Path tracing rules
Causal Analysis using AMOS
Analysis of SEM with latent variables (causal analysis) - General modeling and verification process - Construct operationalization - Confirmatory factor analysis for testing reflective measurement models of latent variables (hypothetical constructs) - Testing of hypothesis using the analysis of covariance
Variants and Extensions
Characteristics of formative measurement models - MIMIC models - Second-order factor analysis (SFA) - multi-group causal analysis and the comparative analysis of causal models in several groups (samples) - Differences between the LISREL approach and the PLS approach - Universal structure modeling
Trainer
Marco Skulschus (born in Germany in 1978) studied economics in Wuppertal (Germany) and Paris (France) and wrote his master´s thesis about semantic data modeling. He started working as a lecturer and consultant in 2002.
Publications
- Grundlagen empirische Sozialforschung ISBN 978-3-939701-23-1
- System und Systematik von Fragebögen ISBN 978-3-939701-26-2
- Oracle PL/SQL ISBN 978-3-939701-40-8
- MS SQL Server - T-SQL Programmierung und Abfragen ISBN 978-3-939701-69-9
Projects
- He works as an IT-consultant and project manager. He developed various Business Intelligence systems for industry clients and the public sector. For several years now, he is responsible for a BI-team in India which is mainly involved in BI and OLAP projects, reporting systems as well as statistical analysis and Data Mining.
Research
He led several research projects and was leading scientist and project manager of a publicly funded project about interactive questionnaires and online surveys.