Likelihood Ratio (LR) Formula

The area under the curve for an ROC plot gives a summary of how well a model works across a variety of thresholds.

A high likelihood ratio indicates that a patient is very likely to have the disease or condition.

In an ROC plot, the x-axis represents the number of False Positives (FPs).

Likelihood ratios are used in medical testing to help physicians decide on the appropriate treatment for a patient.

A low likelihood ratio indicates that a patient is more likely to have the disease or condition.

The True Positive Rate (TPR) is the proportion of answers that were provided correctly as 'true' in an ROC plot.

The False Positive Rate (FPR) is the proportion of answers that were provided incorrectly as 'false' in an ROC plot.

The higher the area under the curve in an ROC plot, the worse the model's performance.

An ROC plot is used to evaluate predictive models based on their ability to distinguish between different classes.

Likelihood ratios can assist in ruling out diseases or conditions based on test results.