This is a five-day course on structural equation modeling (SEM) using Mplus. In this course, SEM experts will teach you about the fundamentals of SEM and various types of longitudinal data analysis techniques, such as growth curves analysis, cross-lagged panel models, and dynamic structural equation modeling (DSEM). The course consists of in-depth lectures and computer lab meeting on the fundamentals of Mplus and on advanced longitudinal models.
Many researchers in the social and behavioural sciences are using, or want to use, Structural Equation Modelling (SEM) to investigate their theories. Mplus is a popular and flexible software package for doing SEM. We offer a 5-day course on learning more about what you are doing in Mplus and about diverse forms of longitudinal analyses in Mplus, where our experts are ready to answer your questions.
On the first day, the focus is on the formulas behind SEM, calculating the number of parameters and degrees of freedom by hand as a way of model checking, interpreting the TECH1 output, when to worry about the default settings in Mplus, model parameterization, and model fit. In the following four days, diverse longitudinal models are discussed, including recent development with respect to cross-lagged panel models, latent growth curve models, latent class growth models, latent transition analysis, and dynamic structural equation models. In addition, the way in which diverse panel data models relate to causal inference is discussed.
On each day there are one or more computer labs in which participants obtain hands-on Mplus experience with the discussed topics and models.
For this course, we assume participants have Mplus experience and basic SEM knowledge (but you do not need to know matrix algebra, calculus, or likelihood theory).
A good preparation for this course is our summer course 'Introduction to Structural Equation Modeling using Mplus' or any other one-week introduction SEM course.
Please note that there are no graded activities included in this course. Therefore, we are not able to provide students with a transcript of grades. You will obtain a certificate upon completion of this course.
Participants are requested to bring their own laptop. If needed, software will be available online.
Lecturers
Prof.dr. Ellen Hamaker, Dr. Beth Grandfield, Jeroen Mulder, Dr. Noémi Schuurman
Target audience
(Research) master students or (post-graduate) researchers who already use Mplus and/or followed a multiple-day introduction into Mplus, for example the USS course ‘Introduction to Structural Equation Modeling using Mplus’. Participants from a variety of fields, including sociology, psychology, education, human development, marketing, business, biology, medicine, political science, and communication sciences, may benefit from the course.
A maximum of 80 participants will be allowed to this course.
The selection will be done on a first-come-first-served basis. Please note that there is always a one-day delay between the registration system and the information on the website about the availability of places.
For an overview of all our summer courses offered by the Department of Methodology and Statistics please click here.
Aim of the course
The main objective of the course is to acquire an expert understanding of longitudinal models as applied in the social and behavioral sciences are analyzed using Mplus.
Study load
Five full days.
Days 1 and 5: The morning session consists of lectures. In the afternoon session, participants obtain hands-on Mplus experience with the discussed topics and models during a computer lab.
Days 2-4: Both the morning and afternoon sessions consist of lectures followed by a computer lab where everyone can practice working with Mplus.
Costs
The tuition fee for PhD students from the Faculty of Social and Behavioural Sciences from Utrecht University will be funded by the Graduate School of Social and Behavioural Sciences.
There are no scholarships available for this course.
Additional information
We also offer tailormade M&S courses and in-house M&S training. If you want to look the possibilities, please contact us at ms.summerschool@uu.nl
Contact details
Team M&S Summer School | E: ms.summerschool@uu.nl