An introduction course to data analysis in R. The focus of this course is on performing analyses in R, not statistical theory. Participants can attend any 1, 2, or 3 days if they have sufficient knowledge to do so.

29 June, 1 July, and 3 July, from 10.00-18.00

Performance of a meta-analytic study can be very valuable within a PhD-project. A meta-analysis enables the PhD-candidate 1) to obtain a good overview of the state-of-the art of the research field of the PhD-project, and 2) to get insight in the way the research problem is tackled, analyzed and reported in existing literature. In this course the core issues of meta-analysis are explained and practiced. 

7 July, 8 July, 9 July, and 10 July, from 13.00-17.00

Functional MRI is one of the most widely used methods in (cognitive) neuroscience. This course will teach the basics of fMRI analysis. Functional MRI (fMRI) is one of the most widely used methods in (cognitive) neuroscience. The analysis of fMRI data is however a multidisciplinary endeavour and requires multiple processing steps. In this 2-day workshop we will teach you the basics of fMRI analysis. 

25 July and 26 July, from 10.00-18.00

Functional MRI is one of the most widely used methods in (cognitive) neuroscience. This course will teach the basics of fMRI analysis. Functional MRI (fMRI) is one of the most widely used methods in (cognitive) neuroscience. The analysis of fMRI data is however a multidisciplinary endeavour and requires multiple processing steps. In this 2-day workshop we will teach you the basics of fMRI analysis. 

22 June, 23 June, 24 June, and 25 June, from 10.00-15.00

In several research fields (inside and outside psychology) nested data are encountered. For example, (1) measurements of children from different classes/schools, (2) measurements of members of different organizations, (3) longitudinal data (subjects measured over time). Nested data result in dependencies, which when not taken into account can mask significant findings (i.e., make them non-significant) or increase false-positive findings. Multilevel models can be used to deal with these dependencies appropriately. In this course we will discuss more advanced topics regarding multilevel modelling (e.g., handling non-linearities and more complex dependence structures, generalized models for nonnormal outcomes and time-series analysis). 

Dates and time yet to be announced.

This course introduces participants to the essentials of qualitative research methods in social science research. It blends a theoretical and practical orientation, with the two-fold goal of providing participants with tools to (a) become thoughtful consumers of social science research that uses qualitative methods; and (b) begin working towards designing and executing sound research projects using qualitative methods. 

Dates and time yet to be announced.

Responsible research and Co-piloting: Dates and time yet to be announced

Information to follow.

Dates and time yet to be announced.

Computational Ethics of Artificial Intelligence: Dates and time yet to be announced

Information to follow.

Dates and time yet to be announced.