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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).
Cstat(x, ...)# S3 method for glm
Cstat(x, ...)
# S3 method for default
Cstat(x, resp, ...)
the linear model
the response variable
further arguments to be passed to other functions.
numeric value
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.
Hosmer D.W., Lemeshow S. (2000) Applied Logistic Regression (2nd Edition). New York, NY: John Wiley & Sons
# NOT RUN {
r.glm <- glm(Survived ~ ., data=Untable(Titanic), family=binomial)
Cstat(r.glm)
# }
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