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.

KH2017

Format

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 KH2017 can be found in KH2017_raw. The rownames of data 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 rownames in 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 usually called timestamps, xpos, and ypos.

Some functions in this package (e.g., mt_time_normalize and mt_average) add additional trajectory arrays (e.g., tn_trajectories and 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.

Details

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.

References

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