dPrime

dPrime

#####################################
# Functions for linguistic research #
# Joseph V. Casillas                #
# Last update: 12-10-2014           #
#####################################

# Calculate d prime in discrimination experiments. 
# Takes a df with the columns:
#    - stimDiff (actual stimuli are different)
#    - stimSame (actual stimuli are the same)
# Each column has responses of 'diff' or 'same'


dPrime <- function(df, stimDiff, stimSame) {

    # Calculate number of same, diff and total responses
    # for the stimuli that were actually different
    stimDiffRdiff <- nrow(df[df$stimDiff == 'diff', ])
    stimDiffRsame <- nrow(df[df$stimDiff == 'same', ])
    stimDiffTotal <- length(df$stimDiff)
    
    # Calculate number of same, diff and total responses
    # for the stimuli that were actually the same
    stimSameRdiff <- nrow(df[df$stimSame == 'diff', ])
    stimSameRsame <- nrow(df[df$stimSame == 'same', ])
    stimSameTotal <- length(df$stimSame)
    
    # Hit rate = the number of correct responses 'diff'
    # when the stimuli were actually diff, divided by 
    # the total number of responses
    hitRate <- stimDiffRdiff / stimDiffTotal
    
    # Miss rate = the number of incorrect responses
    # 'same' when the stimuli were actually diff
    # divided by the total number of responses
    missRate <- stimDiffRsame / stimDiffTotal
    
    # False alarm = the number responses 'diff'
    # when the stimuli were actually the same
    # divided by the total number of responses
    falseAlarm <- stimSameRdiff / stimSameTotal
    
    # Correct rejection = the number of responses
    # same when the stimuli were actually the same
    # divided by the number of total responses
    corrReject <- stimSameRsame / stimSameTotal
    
    # Calculate z-critical values for hit rate
    # and false alarm rate
    zHitRate <- qnorm(hitRate)
    zFalseAlarm <- qnorm(falseAlarm)
    
    # Calculate d prime
    ret = dPrime <- zHitRate - zFalseAlarm
    
    return(ret)
}