24-SEM Basics of Structural Equation Modelling

Tutors: Mark Huisman & Wendy Post
Contact: Nynke Douma (n.h.douma@rug.nl)

Download Course Manual: https://ico-education.nl/wp-content/uploads/2024/05/SEM_Format-ICO-Course-Manual-2023_V2.docx

ECTS: 3

Course description

This workshop will treat three basic elements of structural equation modelling: (1) path analysis, (2) latent variables and factor analysis, and (3) causality. The basic principles of path analysis (including Wright’s tracing rules to find the relations between variables in the model) and drawing path diagrams are introduced, together with the R-software package lavaan, to estimate path models. The use of latent variables in path models and the consequences of using latent variables for estimation (identification) of the models are discussed, as well as the psychometric quality (reliability, validity) of the measurement models for the latent variables. Other important topics are model testing, model comparison and goodness-of-fit measures. These topics are all treated against the background of causal models (causal graphs), where path models are used to inspect causal relationships between concepts (variables). Examples of mediation analyses and Simpson’s paradox will be discussed. To make students more familiar with the procedures and the lavaan-software, exercises are provided. Students will work on these exercises during the workshop, and important findings/answers will be discussed.

Course objectives

The purpose of this workshop is to provide a theoretical introduction to structural equation

modelling, and to gain practical experience with this type of modelling, using the lavaan package for R.

After the workshop, students are able to

•  estimate path models, evaluate the fit, and interpret the results;
• estimate factor models, evaluate the fit, and interpret the results;
• estimate structural equation models, evaluate the fit, and interpret the results;
• analyze longitudinal data with structural equation models;
• compare groups of respondents using structural equation models;
• use the R package lavaan to estimate structural equation models.

Summary of the setup of the course

Date and time	Subjects + preparation (task title and/or literature to read)
11 September 10:00-17:00	Day 1: Path Analysis and Graph Theory
12 September 10:00-17:00	Day 2: Latent Variables and Graph Theory
18 September 10:00-17:00	Day 3: Combining Path Analysis and Confirmatory Factor Analysis
19 September 10:00-17:00	Day 4: Repeated Measures and Groups

Location: Vergadercentrum Vredenburg, Vredenburg 19, Utrecht

Requirements/entry level

Students should have basic knowledge of linear regression and preferably some basic knowledge of R software.

Knowledge of R is not required but is recommended. If you have no or limited knowledge or R, we advise you to check ‘Wickham et al., R for Data Science‘ for free on https://r4ds.hadley.nz/