hybridRecursive takes a data frame of RT data and returns trimmed rt
data. The returned value is the average returned from the nonRecursive
and the modifiedRecursive procedures as described in van Selst &
Jolicoeur (1994).
A data frame with columns containing: participant identification
number ('pptVar'); condition identification, if applicable ('condVar');
response time data ('rtVar'); and accuracy ('accVar'). The RT can be in
seconds (e.g., 0.654) or milliseconds (e.g., 654). Typically, "condition"
will consist of strings. Accuracy must be coded as 1 for correct and 0 for
error responses.
minRT
The lower criteria for acceptable response time. Must be in
the same form as rt column in data frame (e.g., in seconds OR milliseconds).
All RTs below this value are removed before proceeding with SD trimming.
pptVar
The quoted name of the column in the data that identifies
participants.
condVar
The quoted name of the column in the data that includes the
conditions.
rtVar
The quoted name of the column in the data containing reaction
times.
accVar
The quoted name of the column in the data containing accuracy,
coded as 0 or 1 for incorrect and correct trial, respectively.
omitErrors
If set to TRUE, error trials will be removed before
conducting trimming procedure. Final data returned will not be influenced
by errors in this case.
digits
How many decimal places to round to after trimming?
References
Van Selst, M. & Jolicoeur, P. (1994). A solution to the effect
of sample size on outlier elimination. Quarterly Journal of Experimental
Psychology, 47 (A), 631-650.
# NOT RUN {# load the example data that ships with trimrdata(exampleData)
# perform the trimming, returning mean RTtrimmedData <- hybridRecursive(data = exampleData, minRT = 150)
# }