R: C Statistic (Area Under the ROC Curve)

Cstat {DescTools} | R Documentation

## C Statistic (Area Under the ROC Curve)

### Description

Calculate the C statistic, a measure of goodness of fit for binary outcomes in a logistic regression or any other classification model. The C statistic is equivalent to the area under the ROC-curve (Receiver Operating Characteristic).

### Usage

    Cstat(x, ...)

    ## S3 method for class 'glm'
    Cstat(x, ...)

    ## Default S3 method:
    Cstat(x, resp, ...)

### Arguments

`x` | the linear model
`resp` | the response variable
`...` | further arguments to be passed to other functions.

### Details

Values for this measure range from 0.5 to 1.0, with higher values indicating better predictive models. A value of 0.5 indicates that the model is no better than chance at making a prediction of membership in a group and a value of 1.0 indicates that the model perfectly identifies those within a group and those not. Models are typically considered reasonable when the C-statistic is higher than 0.7 and strong when C exceeds 0.8.

Confidence intervals for this measure can be calculated by bootstrap.

### Value

numeric value

### Author(s)

Andri Signorell <andri@signorell.net>

### References

Hosmer D.W., Lemeshow S. (2000) Applied Logistic Regression (2nd Edition). New York, NY: John Wiley & Sons

### See Also

`BrierScore`

### Examples

    r.glm <- glm(Survived ~ ., data=Untable(Titanic), family=binomial)

    Cstat(r.glm)

[Package DescTools version 0.99.28 Index]