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Is the C-statistic the same as AUC?
We let AUC denote the area under the ROC curve, which is equivalent to the c-statistic.
What is Harrell’s C-statistic?
Harrell’s C-index (also known as the concordance index) introduced in Harrell et al. 1982, is a goodness of fit measure for models which produce risk scores. It is commonly used to evaluate risk models in survival analysis, where data may be censored.
What is considered a good C-statistic?
A value below 0.5 indicates a very poor model. A value of 0.5 means that the model is no better than predicting an outcome than random chance. Values over 0.7 indicate a good model. Values over 0.8 indicate a strong model.
How do you find C in statistics?
The c-statistic is equal to the AUC (area under the curve), and can also be calculated by taking all possible pairs of individuals consisting of one individual who experienced a positive outcome and one individual who experienced a negative outcome.
What is the C-statistic used for?
Receiver Operating Characteristic (ROC) curves and the Concordance (C) statistic are often used to assess the ability of a risk factor to predict outcome. We will focus on prediction models for a binary outcome using logistic regression, although exten- sions for censored time to event data are also available.
What is the relationship between the ROC and the AUC?
In the case of a binary outcome and a continuous predictor, the AUC of the ROC or c-index is simply a function of how well the ordered values of the continuous predictor correlate to the corresponding event status.
Is there a correlation between the C index and the AUC?
To more directly answer your question, the censored c-index has no obligatory correlation to the c-index. The censored c-index’s requirement for accurate time ordering is simply not measured in the simple c-index. The effect of censoring and time mean that not all values are used in a censored c-index.
How is AUC related to other statistical measures?
AUC is connected to a variety of well-known statistical measures; the concordance statistic (C-statistic) is the most obvious one, because the two measures are equivalent. As an estimator of the probability of concordance, the C-statistic estimates the concordant probability in a randomly selected pair of subjects.
How to interpret the AUC of a logistic regression?
A model with low sensitivity and low specificity will have a curve that is close to the 45-degree diagonal line. The AUC (area under curve) gives us an idea of how well the model is able to distinguish between positive and negative outcomes. The AUC can range from 0 to 1.