학술논문

Information Graphs Incorporating Predictive Values of Disease Forecasts
Document Type
article
Source
Entropy, Vol 22, Iss 3, p 361 (2020)
Subject
probability
forecast
likelihood ratio
positive predictive value
negative predictive value
diagnostic information
relative entropy
Science
Astrophysics
QB460-466
Physics
QC1-999
Language
English
ISSN
1099-4300
Abstract
Diagrammatic formats are useful for summarizing the processes of evaluation and comparison of forecasts in plant pathology and other disciplines where decisions about interventions for the purpose of disease management are often based on a proxy risk variable. We describe a new diagrammatic format for disease forecasts with two categories of actual status and two categories of forecast. The format displays relative entropies, functions of the predictive values that characterize expected information provided by disease forecasts. The new format arises from a consideration of earlier formats with underlying information properties that were previously unexploited. The new diagrammatic format requires no additional data for calculation beyond those used for the calculation of a receiver operating characteristic (ROC) curve. While an ROC curve characterizes a forecast in terms of sensitivity and specificity, the new format described here characterizes a forecast in terms of relative entropies based on predictive values. Thus it is complementary to ROC methodology in its application to the evaluation and comparison of forecasts.