creating variable that codes for the match/mismatch between two other variables
Hi
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of Jonas Walter
Sent: Monday, February 25, 2013 2:38 PM
To: r-help at r-project.org
Subject: [R] creating variable that codes for the match/mismatch
between two other variables
Dear all,
I have got two vectors coding for a stimulus presented in the current
trial (mydat$Stimulus) and a prediction in the same trial
(mydat$Prediciton), respectively.
By applying an if-conditional I want to create a new vector that
indicates if there is a match between both vectors in the same trial.
That is, if the prediction equals the stimulus.
When I pick out some trials randomly, I get some trials with no match
(mydat$Stimulus[1] != mydat$Prediction[1]) as well as some trials with
a match (mydat$Stimulus[1] == mydat$Prediction[1]).
However, if I apply the following code, each trial is coded as a match.
Why, what do I wrong?
In some blocks, there was no prediction recorded. Therefore, I want
those trials to be labeled differently [that is, match = 7].
Coding-legend:
1 = match
0 = no match
7 = no prediction recorded
The code:
# create varialbe that codes match/mismatch of prediction vs. stimulus
mydat$match <- 0
for (i in seq_along(1:nrow(mydat))) {
# if there is a match, mydat$match[i] = 1 if
(mydat$Stimulus[i] == mydat$Prediction[i]) {
mydat$match = 1
# the next to conditions refer to blocks without prediction recording.
Therefore, the corresponding trials are coded with mydat$match[i] = 7.
} else if (mydat$BlockOrder[i] == 1 & mydat$Block_nr[i] == 1) {
mydat$match = 7
} else if (mydat$BlockOrder[i] == 2 & mydat$Block_nr[i] == 4) {
mydat$match == 7
}
}
Well, why so complicated? (mydat$Stimulus == mydat$Prediction)*1 gives you vector of 1 when there is match and 0 when there is no match. I do not understand your no prediction though. How is no prediction coded? If NA, the resulting vector will have NA in corresponding item too. Regards Petr
# The corresponding dataframe structure: str(mydat) 'data.frame': 9302 obs. of 18 variables: $ BlockOrder : int 1 1 1 1 1 1 1 1 1 1 ... $ Block_nr : num 1 1 1 1 1 1 1 1 1 1 ... $ Trial_nr : int 1 2 3 4 5 6 7 8 9 10 ... $ PreSeq.Length : int 1 2 2 1 1 2 0 2 2 2 ... $ PreSeq : int 21 12 21 20 20 12 0 21 22 11 ... $ Sequence : int 121111 121212 121111 121111 112212 121221 121111 121111 122112 121111 ... $ Category : int 2 1 3 2 1 1 3 3 1 3 ... $ FixCross.Latency : int 1429 1043 1093 1297 1155 1449 1140 1396 1341 1427 ... $ Stimulus : int 2 1 2 2 1 1 1 1 2 1 ... $ RT : int 333 275 378 428 442 388 340 394 414 542 ... $ RT.Button_pressed: int 2 1 2 2 1 1 1 1 2 1 ... $ RT.Accuracy : int 1 1 1 1 1 1 1 1 1 1 ... $ Prediction : int 0 0 0 0 0 0 0 0 0 0 ... $ Confidence : int 0 0 0 0 0 0 0 0 0 0 ... $ ITI : int 1053 1182 1467 1431 1103 1170 1232 1393 1356 1495 ... $ Subject : num 4 4 4 4 4 4 4 4 4 4 ... $ ITruns : num 0 0 0 1 0 1 2 3 0 0 ... $ match : num 1 1 1 1 1 1 1 1 1 1 ... # mydat$match, the new variable, only contains ones. min(mydat$match) [1] 1
max(mydat$match)
[1] 1 # example: row 1699: no match Stimulus - Prediction mydat$Stimulus[1699] == mydat$Prediction[1699] # [1] FALSE # but: mydat$match[1699] # [1] 1 How can I get the right coding? Where is the mistake? Thanks! Best, Jonas Walter [[alternative HTML version deleted]]
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