[R] creating variable that codes for the match/mismatch between two other variables
Jonas Walter
jonas.walter at student.uni-tuebingen.de
Mon Feb 25 16:25:04 CET 2013
Hi Petr,
oh, that's really way more easier than the way I did it. Thanks for the hint!
The problem with "no prediction" is that these cases are already coded
within the "Prediction" variable.
0 codes "no prediction required" while 1 and 2 codes for different
predictions. Therefore, there are no NAs within this variable.
By applying the procedure suggested by you, I would receive 0-coding
for both trials with wrong predictions and trials without any
predictions.
But probably I can change coding within the Prediction-variable prior
to applying your procedure.
Thanks again!
Best,
Jonas
Zitat von PIKAL Petr <petr.pikal at precheza.cz>:
> 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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