12 August 2016
Introduction to Structural Equation Modeling Framework: Confirmatory Factor Analysis with Mplus
The course focuses on Measurement Models and their application in the broader Structural Equation Modeling (SEM) Framework. We will show how a theoretical model represented through measurement models can be applied to empirical data and estimations for its fit can be derived. Confirmatory Factor Analysis (CFA) as an important and basic aspect of the SEM-framework is the core learning aspect of this course and as such a necessary preparation for the courses “Understanding and Modelling Measurement Error in Social Surveys” and “Testing Survey Data for Measurement Equivalence Across Countries and Time” in the subsequent weeks. CFA is also a necessary conceptual precondition to understanding and application of the structural aspect of SEM, path modeling. Therefore, the content deals with concepts and applications of CFA such as proving the construct validity and reliability of a measurement model and the interpretation of calculated results. The topics addressed in the course include different modeling techniques of CFA: single measurement models, Simultaneous CFA (SCFA), the Multiple Group Comparison of the CFA (MGCFA), the higher-order CFA - and if the time resources allow it - also Longitudinal Models. The course will introduce participants to practical examples involving the commonly used SEM software package Mplus. For data preparation we will use mainly SPSS, but we will also be able to accommodate needs of STATA-users.
You can find the full syllabus of the course with complete information on the topics, literature, and day-to-day schedule on https://training.gesis.org.
Prof. Dr. Jost Reinecke is professor of quantitative methods of empirical social research at the Faculty of Sociology at the University of Bielefeld, Germany;
Georg Kessler works as a lecturer at the University of Vienna in the department of Sociology an
Participants will find the course useful if they:
a) On the level of their research questions
- work with models that involve a complex structure of variables and their relationships to each other;
- have a strong deductive framework and want to verify theoretical assumptions derived from substantive theories;
- need information on measurement quality (validity and reliability testing).
b) On a more basic level
- want to get an introduction into Structural Equation Model (SEM)-Framework;
- have had prior experience with SEM, but no formal training;
- have had prior training, but still find the whole matter rather complicated;
- want to get acquainted with the software Mplus;
- wish to attend the course “Understanding and Modelling Measurement Error in Social Surveys” or/and “Testing Survey Data for Measurement Equivalence Across Countries and Time” in the subsequent weeks.
Although this course is introductory, the theoretical input of the course is dense enough, so that advanced users can also find it useful to “freshen-up” their knowledge.
- familiarity with and a conceptual/mathematical understanding of variance, covariance, correlation, standardization, hypothesis testing (t-test, chi-square), and regression analysis [for compact refreshing we recommend http://davidmlane.com/hyperstat/];
- basic knowledge of matrix notation [a short refresher can be found on https://www.youtube.com/watch?v=G16c2ZODcg8];
- basic knowledge of solving a linear equation system;
- familiarity with writing syntax (Mplus input - as taught in the class - is syntax only) [we recommend to look into chapter 5 of http://www.statmodel.com/ugexcerpts.shtml]
- handling of system files (.sps; .dta; …) and transformation to portable or ASCII-data files (.dat; .csv; .txt; …) [a good preparation is to import .txt-files into SPSS and use SPSS-syntax to get data].
As introductory reading we also recommend to study the chapters 1 to 3 in Brown, T. A. (2006). Confirmatory factor analysis for applied research.
By the end of the course participants will:
- know how to apply SEM in the context of a research question;
- comprehend the mathematical and statistical foundation of SEM;
- have an understanding of the Mplus command structure and practice with the program’s basic commands;
- be able to read, understand and interpret an Mplus output;
- transfer the theoretical knowledge to applied research projects;
- in general be enabled to acquire the set of skills they need for their individual projects;
- be prepared to follow the the course “Understanding and Modelling Measurement Error in Social Surveys” or/and “Testing Survey Data for Measurement Equivalence Across Countries and Time” in the subsequent weeks.
- Certificate of attendance issued upon completion.
- 2 ECTS points via the University of Mannheim for regular attendance and satisfactory work on daily assignments (EUR 20).
- 4 ECTS points via the University of Mannheim for regular attendance and satisfactory work on daily assignments and for submitting a paper/report of about 5000 words to the lecturer(s) up to 4 weeks after the end of the summer school (EUR 50).
EUR 250: Student/PhD student rate.
EUR 350: Academic/non-profit rate.
Early bird discount: EUR 50 for applicants who book and pay by April 30.
The rates include the tuition fee, course materials, the academic program, access to library and IT facilities, coffee/tea, and a number of social activities.
10 DAAD scholarships are available via the Center for Doctoral Studies in Social and Behavioral Sciences (CDSS) at the University of Mannheim.