GESIS Training Courses

Short Course B: Introduction to Data Analysis Using Mplus

Dr. Matthias Blümke, Dr. Clemens Lechner, Prof. Dr. Daniel Danner

Datum: 02.08 - 03.08.2018 ics-Datei

Referenteninformationen - Dr. Matthias Blümke

Referenteninformationen - Dr. Clemens Lechner

Referenteninformationen - Prof. Dr. Daniel Danner


This short course introduces the statistical software Mplus and demonstrates the basic programming skills for analyzing multivariate statistical problems such as structural equation models (SEM) with Mplus. Mplus is one of the most widely used software packages for analysing such latent variable models. The main objective of this course is to understand the basic features of Mplus, the syntax of its code, and the appropriate work flow. Participants will learn how to prepare and load their data, become familiar with the structure of Mplus input and output files, and learn how to write Mplus syntax of simple and more complex latent variable models.  Rather than introducing specific statistical models, the course will focus on the more general task of handling the Mplus software and equip participants with the skills needed to implement their own statistical models. The participants are expected to be familiar with the general idea of statistical analysis, regression models, and sound knowlegde about factor analysis. Basic knowledge about latent variable modeling and structural equation modeling is helpful. Aspects such as specifying models, choosing appropriate estimation methods, and handling missing data will be covered.
For a full length syllabus of this course, please click here.



Participants will find the course useful if:
  • they want to use latent variables or apply structural equation modelling
  • they are interested in extending their technical/programming skills and are curious about a powerful statistical software
  • they attend the course “Introduction to Structural Equation Modelling” in week 1 of the summer school


By the end of the course participants will:
  • know how to prepare data for Mplus analysis
  • be able to understand the Mplus syntax and write Mplus code for basic and more advanced (latent variable) models
  • be able to interpret Mplus output
  • be able to translate fundamental statistical aspects of SEM into Mplus code


  • Good knowledge of basic uni- and multivariate statistics (especially regression and factor analysis)
  • At least basic understanding of latent variables and structural equation modeling (SEM)
  • No previous experience with Mplus required