We offer a 5-day course on how to perform basic SEM analyses using Mplus. The main objective of this course is to learn how to analyse several models with Mplus (e.g. path models, multiple group models, mediation and moderation, confirmatory factor analysis, and longitudinal models). No previous knowledge of Mplus is assumed, but prior knowledge of SEM, although not mandatory, will make this course more useful.
Many researchers in the social and behavioral 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 how to perform basic SEM analyses using Mplus.
The course starts with an introduction on how to use Mplus to perform regression analysis and how to ‘communicate’ with Mplus (e.g., how to specify a model, and how to deal with error messages). In the following days basic models relevant for social scientists will be discussed, including multiple group models, confirmatory factor analysis, and cross-lagged panel models, and important topics such as moderation, mediation and testing for measurement invariance are covered. On the last day participants can meet with Mplus experts for individual consultation, and work on their own data. On the other days, the morning session consists of lectures, and the afternoon session of a computer lab where participants practice with Mplus.
Researchers are expected to have a basic knowledge of regression analysis and exploratory factor analysis (i.e., principal component analysis). These techniques are discussed in most books on multivariate statistics (e.g., Andy Field: Discovering Statistics; Tabachnick and Fidell: Using multivariate statistics). Some knowledge of SEM and software like AMOS, LISREL, Mx or EQS is helpful, but not mandatory. If you have no experience with SEM, please read the following paper: Hox, J. J. & Bechger, T.M. (2007). An introduction to structural equation modelling. Family Science Review, 11, 354-373. Accessible via www.joophox.net.
No previous knowledge of Mplus is assumed. You do not need to have any knowledge on matrix algebra, calculus, or likelihood theory.
A good follow up is our Summer School course ‘Advanced course on using Mplus’
Please note that there is always the possibility that we have to change the course pending COVID19-related developments. The exact details, including a day-to-day program, will be communicated 6 weeks prior to the start of the course.
Prof. dr. Ellen Hamaker, Dr. Beth Grandfield
Participants (Research Master Students, PhD students, or post-graduate researchers) 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 in this course. Please note that the selection for this course will be done on a first-come-first-served basis.
Aim of the course
The main objective of the course is to acquire a basic understanding of how to use Mplus for SEM as applied in the social and behavioral sciences. Moreover, participants will learn how to analyse datasets with Mplus, to interpret the output and to report the results.
For an overview of all our summer school courses offered by the Department of Methodology and Statistics please click here.
Days 1-4: morning session consists of lectures, and the afternoon session of a computer lab where everyone can practice working with Mplus. Day 5: individual consultations with Mplus experts and room to work on your own data.
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.
You can choose between two options for participating in this course, but please note that there is always the possibility that we have to change the course pending COVID19-related developments:
- If you choose the livestream option, you will get a discount on the course fee since we will not provide lunch then. The lectures will be broadcasted in Central European Summer Time via a livestream (not recorded). Participants can ask questions via the chat which will be moderated by a second lecturer who will either directly answer your questions via the chat or ask your questions to the first lecturer during class. You will also receive online support during the group computer labs from our team. Additionally, Q&A sessions will be organised so you will benefit from our normal high level expertise while enjoying the class from the comfort of your own chair.
- If you choose the campus option, you will be able to attend the lectures and computer labs at our campus. Of course, we will follow all COVID19-guidelines that hold at the time of the start of your course. We will keep you updated about the newest developments (see also https://www.uu.nl/en/information-coronavirus). Note that, at the moment, it is unclear how many participants will be allowed in our lecture rooms. Therefore, if you register for the campus option, we will also register you for the livestream option such that you are guaranteed a spot via the livestream option (and at first, send an invoice for this option only). We will put you ‘on hold’ for the campus option until we have more information about how many participants are allowed in our lecture rooms. As soon as we hear from the university, we will contact you and send you a second invoice for the part of the fee related to catering and campus registration.
If you are interested in the campus option, let us know via a message in the application form under ‘Student Comment’.
The physical course costs €720, but if you participate via the livestream you will get a 100 euro discount. Note that if you choose the campus option, you will be asked to first pay the livestream-fee (€620) and, when we have permission from the university to actually organise classes on location, we will send a second invoice for the remainder of the fee. This way, you will be ensured to have at least a spot for the livestream.
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.
Irma Reyersen | E: email@example.com