This function reads IAT files as generated by the OpenSesame script available at [INSERT URL].
processOpenSesameIAT(dataPath,
blocks.sizes = c(18, 36, 48, 36, 48),
blocks.congruent = c(2, 3),
blocks.incongruent = c(4, 5),
blocks.realTrials = c(3, 5),
blocks.practiceTrials = c(2, 4),
congruentLarger = TRUE,
responseTime.min = 400,
responseTime.max = 2500,
responseTime.penalty = 600,
outputFile = NULL,
wideOutputFile = NULL,
showLog = TRUE,
filenameRegEx = "subject-(\\d+)(\\w+)\\.csv",
regExValues = c("subject","session"),
participantVarName = "subject",
taskVarName = "session",
openSesameVarNames = list(correct = "correct",
response_time = "response_time"),
stimulusSelectionVarName = NULL,
stimulusSelectionValues = NULL,
roundOutput = 6,
decimalSeparator = ".",
inputDecimalSeparator = ".",
inputfileSelectionColumns = NULL,
inputfileSelectionValues = NULL)A directory containing the .csv files that OpenSesame provides.
A vector containing the number of trials of each block.
A vector containing the numbers of the congruent blocks.
A vector containing the numbers of the incongruent blocks.
A vector containing the numbers of the real trials.
A vector containing the numbers of the practice trials.
Whether the response latencies for the congruent trials (TRUE) or the incongruent trials (FALSE) are expected to be larger. This simply multiplies the final D600 measures with -1.
Minimum number of milliseconds of response time (all shorter times will be removed).
Maximum number of milliseconds of response time (all longer times will be replaced with this number).
Penalty in milliseconds to add to the response times for incorrect responses.
If specified, the aggregated datafile is stored in this file.
If specified, the wide version of the datafile will be stored in this file.
Boolean; if TRUE, shows the log (is stored in the resulting object anyway).
Regular expression describing the filenames. This has two purposes.
First, only files matching this regular expression will be processed
(note that you can set it to NULL to process all files). Second,
by using "\1", "\2", etc, matched patterns can be
extracted from the filenames and stored as variables in the final
datafile (see sub for more information on regular expression
matching). The default pattern, "subject-(\d+)(\w+)\.csv",
which is read by R as "subject-(\d+)(\w+)\.csv" (because the
backslash is the escape symbol, double backspaces are needed to specify
one backspace, see Quotes), assumes that all filenames start
with 'subject-', followed by the subject number ("\d+"
matches one or more digits), immediately followed by one or more letters
and digits ("\w+" matches one or more letters or digits)
indicating the session that the datafile pertains to. If you only have
subject numbers, you'd use "subject-(\d+)\.csv" or perhaps
"subject-(\w+)\.csv" if the subjects could also have letters
in their identifiers. Note that you have to include the variable names
of each of these extractable patterns in regExValues!
Here, the names of the variables extracted using the regular expression
specified in filenameRegEx are provided. Must of course have the
same length as the number of patterns specified in filenameRegEx,
and in the same order.
Variable name of the variable identifying participants and tasks (usually extracted from the filename, so should be a value in regExValues). Tasks are usually different within-subject conditions.
A list with the two elements 'correct' and 'response_time', which should be the variable names that OpenSesame used to write, for each trial, whether the response was correct or not ('correct') and what the response time was ('response_time');
These arguments can be used to specify a subset of stimuli to process. Specify which column contains the values to select in stimulusSelectionVarName, and specify the value(s) to select in stimulusSelectionValues.
Number of digits to round the output to. This is useful for importing into a program that doesn't quite get how storing numbers works, such as SPSS or Excel; they sometimes don't manage to import numbers with many decimals.
When working with e.g. Excel, it can be easier to just specify the decimal separator rather than switch Excel's (and therefore Windows') locale.
The decimal separator to specify to read.csv when reading the data files.
This functionality still has to be implemented. Once implemented, these arguments can be used to specify a column, and a (set of) value(s) in that column to use to select which rows to process (also see stimulusSelectionVarName and stimulusSelectionValues).
An object with the raw files, the processed files, and the file converted
to wide format. But most users will probably specify outputFile
and/or wideOutputFile to just export the output files directly.
Note that this function was developed to read the OpenSesame IAT datafiles
created by the OpenSesame script developed by Kenny Wolfs, Jacques van
Lankveld, and Frederik van Acker at the Open University of the Netherlands.
If you use a different version (for example, the one contributed to the
OpenSesame paradigm repository by Hansika Kapoor, see
http://osdoc.cogsci.nl/3.0/standard-tasks/#implicit-association-test-iat),
you will have to specify the variable names you specified to OpenSesame
for the response time and for whether the response was correct in
openSesameVarNames. For example, if you use Hansika's IAT task,
you'll have to specify openSesameVarNames = list(correct = "correct",
response_time = "avg_rt")
Similarly, of course you will probably have to specify the number of trials per block etc. Also, you may want to set showLog to FALSE, as the logging is quite detailed.
Mathot, S., Schreij, D., & Theeuwes, J. (2012). OpenSesame: An open-source, graphical experiment builder for the social sciences. Behavior Research Methods, 44(2), 314-324. doi:10.3758/s13428-011-0168-7
Kapoor, H. (2015). The creative side of the Dark Triad. Creativity Research Journal, 27(1), 58-67. doi:10.1080/10400419.2014.961775.
# NOT RUN {
# }
# NOT RUN {
### This will process all files in the specified directory, but not
### export anything
processed <- processOpenSesameIAT("C:/directory/with/datafiles");
### This will export both the aggregated datafile and the wide datafile
processed <- processOpenSesameIAT("C:/directory/with/datafiles",
outputFile="C:/directory/aggregated.csv",
wideOutputFile="C:/directory/wide.csv");
# }
# NOT RUN {
# }
Run the code above in your browser using DataLab