Establishing correlations among common inhibition tasks such as Stroop or flanker tasks has been proven quite difficult despite many attempts. It remains unknown whether this difficulty occurs because inhibition is a disparate set of phenomena or whether the analytical techniques to uncover a unified inhibition phenomenon fail in real-world contexts.

In this internship, you will explore whether this state of affairs can be improved by disentangling different types of inhibition that are in play within one task. In a recent unpublished study, it has been shown that accounting for sequential effects within an experiment can improve the reliability of individual differences. In the internship, you will first try to replicate this finding in an open-access SQL data base of existing attentional control studies. If we can establish the finding, and depending on your interests and experience, you will proceed by implementing a simple multilevel model that accounts for the sequential effect to see if reliability is increased and correlations across tasks can be established after all.

Requirements:

• Basic understanding of concepts such as reliability and statistical analyses like within-subjects ANOVA.
• Basic Knowledge of the programming language R (and willingness to work on R skills) is a plus.
• Basic knowledge of Bayesian analysis is a plus.

There is funding to make this internship into an RA position.

I am looking forward to meet with any interested students!