Pascal J. Kieslich, Felix Henninger, Dirk U. Wulff, Jonas M. B. Haslbeck, Michael Schulte-Mecklenbeck
Mouse-tracking: A practical guide to implementation and analysis

Pp. 111-130 in: Michael Schulte-Mecklenbeck, Anton Kühberger, Joseph G. Johnson (Eds.): A Handbook of Process Tracing Methods. 2nd ed. 2019. New York, NY: Routledge

This chapter provides an introduction to the collection, analysis, and visualization of mouse-tracking data using free, open-source software. It shows how to create mouse-tracking experiments using the graphical experiment builder OpenSesame in combination with the mousetrap plugin. The chapter demonstrates how a mouse-tracking experiment can be created in OpenSesame. The mouse sensitivity settings cannot be adjusted directly within OpenSesame, but need to be set in the computer’s system preferences. The mousetrap R package represents mouse-tracking data in a specialized data structure, a mousetrap data object. This allows the package to store and process mouse trajectories efficiently, and to link them to other information collected during the study. In addition to curvature, mouse-tracking studies have also used the complexity of the movement as an indicator of response competition. In mouse-tracking studies, participants’ cursor movements are recorded as they choose between different options represented as buttons on a computer screen.