{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T13:56:14Z","timestamp":1771682174237,"version":"3.50.1"},"reference-count":19,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T00:00:00Z","timestamp":1584662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/e22030361","type":"journal-article","created":{"date-parts":[[2020,3,23]],"date-time":"2020-03-23T04:03:01Z","timestamp":1584936181000},"page":"361","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Information Graphs Incorporating Predictive Values of Disease Forecasts"],"prefix":"10.3390","volume":"22","author":[{"given":"Gareth","family":"Hughes","sequence":"first","affiliation":[{"name":"SRUC, The King\u2019s Buildings, Edinburgh EH9 3JG, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer","family":"Reed","sequence":"additional","affiliation":[{"name":"Department of Plant Pathology, University of California, Davis, CA 95616, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6346-9461","authenticated-orcid":false,"given":"Neil","family":"McRoberts","sequence":"additional","affiliation":[{"name":"Department of Plant Pathology, University of California, Davis, CA 95616, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1038\/scientificamerican1000-82","article-title":"Better decisions through science","volume":"283","author":"Swets","year":"2000","journal-title":"Sci. Am."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1007\/BF01877054","article-title":"Calibration and verification of risk algorithms using logistic regression","volume":"102","author":"Yuen","year":"1996","journal-title":"Eur. J. Plant Pathol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/S0261-2194(98)00035-0","article-title":"Forecasting Sclerotinia stem rot in spring sown oilseed rape","volume":"17","author":"Sigvald","year":"1998","journal-title":"Crop Prot."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1046\/j.0032-0862.2002.00741.x","article-title":"Bayesian analysis of plant disease prediction","volume":"51","author":"Yuen","year":"2002","journal-title":"Plant Pathol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1146\/annurev-phyto-080516-035342","article-title":"The evidential basis of decision making in plant disease management","volume":"55","author":"Hughes","year":"2017","journal-title":"Annu. Rev. Phytopathol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10658-005-1229-5","article-title":"Botanical epidemiology: Some key advances and its continuing role in disease management","volume":"115","author":"Madden","year":"2006","journal-title":"Eur. J. Plant Pathol."},{"key":"ref_7","unstructured":"Theil, H. (1967). Economics and Information Theory, North-Holland."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1016\/j.cropro.2008.02.006","article-title":"A Bayesian approach to assess the accuracy of a diagnostic test based on plant disease measurement","volume":"27","author":"Makowski","year":"2008","journal-title":"Crop Prot."},{"key":"ref_9","unstructured":"Friedland, D.J., Go, A.S., Ben Davoren, J., Shilpak, M.G., Bent, S.W., Subak, L.L., and Mendelson, T. (1998). Refining probability: An introduction to the use of diagnostic tests. Evidence-Based Medicine: A Framework for Clinical Practice, McGraw-Hill\/Appleton & Lange."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1002\/(SICI)1097-0258(20000315)19:5<649::AID-SIM371>3.0.CO;2-H","article-title":"Comparing diagnostic tests: A simple graphic using likelihood ratios","volume":"19","author":"Biggerstaff","year":"2000","journal-title":"Stat. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1094\/PHYTO.2003.93.4.428","article-title":"Risk assessment models for wheat Fusarium head blight epidemics based on within-season weather data","volume":"93","author":"Madden","year":"2003","journal-title":"Phytopathology"},{"key":"ref_12","first-page":"1","article-title":"Entropy\u2014new editor-in-chief and outlook","volume":"11","year":"2009","journal-title":"Entropy"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2257","DOI":"10.1002\/sim.1835","article-title":"Advantages to transforming the receiver operating characteristic (ROC) curve into likelihood ratio co-ordinates","volume":"23","author":"Johnson","year":"2004","journal-title":"Stat. Med."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1002\/sim.2028","article-title":"Letter to the editor","volume":"24","author":"Fosgate","year":"2005","journal-title":"Stat. Med."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1002\/(SICI)1097-0258(20000229)19:4<453::AID-SIM350>3.0.CO;2-5","article-title":"What do we mean by validating a prognostic model?","volume":"19","author":"Altman","year":"2000","journal-title":"Stat. Med."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1094\/PHYTO-01-17-0023-FI","article-title":"Evaluation of probabilistic disease forecasts","volume":"107","author":"Hughes","year":"2017","journal-title":"Phytopathology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2","article-title":"Verification of forecasts expressed in terms of probability","volume":"78","author":"Brier","year":"1950","journal-title":"Mon. Weather Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3387","DOI":"10.1175\/2010MWR3229.1","article-title":"Kullback-Leibler divergence as a forecast skill score with classic reliability-resolution-uncertainty decomposition","volume":"138","author":"Weijs","year":"2010","journal-title":"Mon. Weather Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1055\/s-0038-1634294","article-title":"The use of information graphs to evaluate and compare diagnostic tests","volume":"41","author":"Benish","year":"2002","journal-title":"Methods Inform. Med."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/22\/3\/361\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:10:17Z","timestamp":1760173817000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/22\/3\/361"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,20]]},"references-count":19,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["e22030361"],"URL":"https:\/\/doi.org\/10.3390\/e22030361","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,20]]}}}