A data object of class "mousetrap" with the imported and preprocessed mouse-tracking data from Kieslich & Henninger (2017). More information about the study and raw data can be found in KH2017_raw.
A mousetrap data object is a list containing at least the following objects:
data: a data.frame containing the trial data (from
which the mouse-tracking data columns have been removed). More
information about the content of the trial data in
be found in KH2017_raw. The rownames of
correspond to the trial identifier. For convenience, the trial identifier
is also stored in an additional column called "mt_id".
trajectories: an array containing the raw
mouse-tracking trajectories. The first dimension represents the different
trials and the dimension names (which can be accessed using
rownames) correspond to the trial identifier (the same identifier
that is used as the
data). The second dimension
corresponds to the samples taken over time which are included in
chronological order. The third dimension corresponds to the different
mouse-tracking variables (timestamps, x-positions, y-positions) which are
Some functions in this package (e.g., mt_time_normalize and
mt_average) add additional trajectory arrays (e.g.,
av_trajectories) to the mousetrap data
object. Other functions modify the existing arrays (e.g.,
mt_derivatives adds distance, velocity, and acceleration
to an existing dataset). Finally mt_measures adds an
additional data.frame with mouse-tracking measures to it.
The raw dataset (KH2017_raw) was filtered keeping only correctly answered trials. The filtered dataset was imported using mt_import_mousetrap. Trajectories were then remapped using mt_remap_symmetric so that all trajectories end in the top-left corner and their starting point was aligned to a common value (0,0) using mt_align_start.
Kieslich, P. J., & Henninger, F. (2017). Mousetrap: An integrated, open-source mouse-tracking package. Behavior Research Methods, 49(5), 1652-1667. doi:10.3758/s13428-017-0900-z
Dale, R., Kehoe, C., & Spivey, M. J. (2007). Graded motor responses in the time course of categorizing atypical exemplars. Memory & Cognition, 35(1), 15-28. doi:10.3758/BF03195938