What is ROC curve in SAS?

What is ROC curve in SAS?

An ROC curve graphically summarizes the tradeoff between true positives and true negatives for a rule or model that predicts a binary response variable. An ROC curve is a parametric curve that is constructed by varying the cutpoint value at which estimated probabilities are considered to predict the binary event.

What is ROC curve in logistic regression?

ROC curves in logistic regression are used for determining the best cutoff value for predicting whether a new observation is a “failure” (0) or a “success” (1). Your observed outcome in logistic regression can ONLY be 0 or 1. The predicted probabilities from the model can take on all possible values between 0 and 1.

Can you use the ROC statement in Proc logistic?

In summary, you can use the ROC statement in PROC LOGISTIC to generate ROC curves for models that were computed outside of PROC LOGISTIC. All you need are the predicted probabilities and observed response for each observation.

How to compare two ROC curves in SAS?

You can also overlay and compare two or more ROC curves and use the ROCCONTRAST statement to analyze the difference between areas under the curves. Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software.

How to create customized odds ratios in Proc logistic?

The UNITS statement is specified to produce customized odds ratio estimates for a change of 10 years in the age variable, and the CLODDS=PL option is specified to produce profile-likelihood confidence limits for the odds ratio. The ODS Graphics statement and the PLOTS= option produce graphical displays of the ROC curve of the model fit.

How to create and compare ROC curves for any predictive model?

You might want to overlay and compare ROC curves from multiple predictive models (either from PROC LOGISTIC or from other sources). PROC LOGISTIC can do that as well. You just need to merge the various predicted probabilities into a single SAS data set and then specify multiple ROC statements, as follows: