Description Usage Arguments Details Value Author(s) Examples

Calculate concordance and discordance percentages for a logit model

1 | ```
Concordance(actuals, predictedScores)
``` |

`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. |

Calculate the percentage of concordant and discordant pairs for a given logit model.

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.

Selva Prabhakaran [email protected]

1 2 | ```
data('ActualsAndScores')
Concordance(actuals=ActualsAndScores$Actuals, predictedScores=ActualsAndScores$PredictedScores)
``` |

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