Introduction to Structural Equation Modeling in Mplus (with Christoph Helm)
Autor:
Ovidiu Ioan Moisescu
30 Mai 2023 -
31 Mai 2023
We invite UBB-FSEGA teaching staff, researchers and PhD students to attend the workshop on Structural Equation Modeling (SEM): Basic Topics and Practical Issues, delivered by Christoph Helm, Chaired Professor at Johannes Kepler University Linz, Austria and Research Professor at the Institute for the Management and Economics of Education (IBB) University of Education Zug, Switzerland.
Christoph Helm’s research interests focus on school effectiveness and instructional quality, using large-scale assessments and statistical complex techniques (e.g., multilevel structural equation modelling). He is the author of more than 50 papers, with the most influential ones in the field of schooling and assessment during the COVID-19 pandemic. To find out more about him and read some of his published papers check his Research Gate or Google Scholar profile.
Workshop schedule
Tuesday, 30 May 2023, 12.00-16.00
12.00-12.30: Warm up
12.30-14.00: Theoretical background on Structural Equation Modeling
14.00-15.00: Preparing data for Mplus
15.00-16.00: Introduction to Mplus command language
Wednesday, 31 May 23, 12.00-16.00
12.00-13.00: Implementing Structural Equation Modeling in Mplus
13.00-14.00: Theory and practice on Mediation Models in Mplus
14.00-15.00: Theory and practice on Moderation Models in Mplus
15.00-16.00: Individual practice in Mplus
Workshop location
Babeș-Bolyai University
Faculty of Economics and Business Administration
Room
118
Requirements for participation
UBB-FSEGA teaching staff, researchers and PhD students need to register using the
FSEGA Online platform by
Monday, 29 May 2023.
Special note: Participants need to download on their laptops a trial version of Mplus from
HERE
Why Structural Equation Modeling?
In many social science disciplines, researchers are not only interested in the effects of directly observable variables (e.g., income), but also in the effects of variables that are not directly observable (e.g., job satisfaction). The measurement of variables that are not directly observable presents researchers with the challenge of capturing the unobservable, true value using instruments such as questionnaire scales. The omission of scales (= measurement with only one item) or the use of poorly constructed scales can lead to strong measurement errors, i.e., systematically biased estimates. This in turn can lead to highly biased effects and correspondingly incorrect interpretations and conclusions. To avoid this and to do analyses ba
sed on true values, social scientists often resort to the method of structural equation modeling (SEM). In the workshop, I give an introduction to SEM using data and constructs from work and organizational psychology. Moreover, the workshop offers the opportunity to learn and test the method on one’s own data.
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