read_mt reads raw data that was collected using
MouseTracker (Freeman & Ambady, 2010)
and stored as a file in the ".mt" format. If multiple files should be read
into R, read_mt can be used in combination with the
read_bulk function from the
readbulk package (see
Examples). After reading the data into R, mt_import_wide can be used
to prepare the trajectory data for analyses using the mousetrap library. The
current version of read_mt has been tested with data from MouseTracker
Version 2.84 - but please be sure to double-check.
read_mt(file, columns = "all", add_trialid = FALSE, add_filename = FALSE)a character string specifying the filename of the .mt file.
either 'all' or a character vector specifying the to be extracted variables. Defaults to 'all' in which case all existing variables will be extracted.
boolean specifying whether an additional column containing the trial number should be added.
boolean specifying whether an additional column containing the file name should be added.
A data.frame with one row per trial. Variables are ordered according to columns, x-coordinates, y-coordinates, and timestamps.
Freeman, J. B., & Ambady, N. (2010). MouseTracker: Software for studying real-time mental processing using a computer mouse-tracking method. Behavior Research Methods, 42(1), 226-241.
read_bulk from the readbulk package for reading and
combining multiple raw data files.
mt_import_wide to prepare the imported data for analyses in mousetrap.
if (FALSE) {
# Read a single raw data file from MouseTracker
# (stored in the current working directory)
mt_data_raw <- read_mt("example.mt")
# Use read_bulk to read all raw data files ending with ".mt" that are
# stored in the folder "raw_data" (in the current working directory)
library(readbulk)
mt_data_raw <- read_bulk("raw_data", fun=read_mt, extension=".mt")
# Import the data into mousetrap
mt_data <- mt_import_wide(mt_data_raw)
}