On this page you can find all the courses and tracks offered by the Utrecht Summer School. Detailed information is published on all individual course pages.
5 course(s) found
As an advanced training in Cognitive Neuropsychology, the course aims to teach PhD students how to collect and interpret patient data in order to test cognitive theories and build cognitive models. The emphasis will be on 'doing research'. Candidates will get an acquaintance with standard neuropsychological testing, will be shown examples of patients cases, case statistics and will build, run and analyse their own experiment. A special training…
During this course, we discuss social scientific theories and empirical research on international migration, the socio-economic and cultural integration of immigrants and their children, and reactions of the host society. Migration has made European countries ethnically and culturally more diverse. While migrants try to find their way in a new and sometimes hostile environment, host populations also have to adapt to migrants and the new…
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.
In this e-learning course, we will cover the basics of structural equation modeling (SEM) using the R package lavaan. Participants will learn how to interact with the lavaan software and how to run common types of SEMs (e.g., path models, confirmatory factor analyses, latent regression models, multiple group models) using lavaan. No prior knowledge of lavaan is necessary, but some experience with R and SEM (although not strictly required) is…
This course offers an elaborate introduction to statistical programming with R. Students learn to operate R, form pipelines for data analysis, make high quality graphics, fit, assess, and interpret a variety of statistical models, and do advanced statistical programming. The statistical theory in this course covers t-testing, regression models for linear, dichotomous, ordinal, and multivariate data, statistical inference, statistical learning,…