Calculate concordance and discordance percentages for a logit model
Usage
Concordance(actuals, predictedScores)
Arguments
actuals
The actual binary flags for the response variable. It can take a numeric vector containing values of either 1 or 0, where 1 represents the 'Good' or 'Events' while 0 represents 'Bad' or 'Non-Events'.
predictedScores
The prediction probability scores for each observation. If your classification model gives the 1/0 predcitions, convert it to a numeric vector of 1's and 0's.
Value
a list containing percentage of concordant pairs, percentage discordant pairs, percentage ties and No. of pairs.
Concordance The total proportion of pairs in concordance. A pair is said to be concordant when the predicted score of 'Good' (Event) is greater than that of the 'Bad'(Non-event)
Discordance The total proportion of pairs that are discordant.
Tied The proportion of pairs for which scores are tied.
Pairs The total possible combinations of 'Good-Bad' pairs based on actual response (1/0) labels.
Details
Calculate the percentage of concordant and discordant pairs for a given logit model.