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)

Arguments

file

a character string specifying the filename of the .mt file.

columns

either 'all' or a character vector specifying the to be extracted variables. Defaults to 'all' in which case all existing variables will be extracted.

add_trialid

boolean specifying whether an additional column containing the trial number should be added.

add_filename

boolean specifying whether an additional column containing the file name should be added.

Value

A data.frame with one row per trial. Variables are ordered according to columns, x-coordinates, y-coordinates, and timestamps.

References

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.

See also

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.

Examples

# NOT RUN {
# 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)
# }