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Statistical Issues in Prediction: what can be learned for individualized predictive medicine?

dc.date.accessioned2019-10-24T14:01:32Z
dc.date.available2019-10-24T14:01:32Z
dc.date.issued2010
dc.identifier.urihttp://publications.mfo.de/handle/mfo/3164
dc.description.abstractError is unavoidable in prediction. And it is quite common, often sizable, and usually consequential. In a clinical context, especially when dealing with a terminal illness, error in prediction of residual life means that patients and families are misinformed about their illness, that they may take foolish actions as a result, and that they may be given inappropriate or needlesly painful treatments or denied appropriate ones. In meteorology, error in prediction of storm paths or extreme events can have devastating consequences. In finance and economics, major policy decisions are taken on the basis of predictions and forecasts. Rational approaches to reduce and assess error in prediction are presented. Ideas are introduced how to relate these statistical strategies with clinical and medical concepts in particular and how to integrate ideas from apparently different areas.
dc.titleStatistical Issues in Prediction: what can be learned for individualized predictive medicine?
dc.identifier.doi10.14760/OWR-2010-6
local.series.idOWR-2010-6
local.subject.msc62
local.subject.msc92
local.sortindex604
local.date-range24 Jan - 30 Jan 2010
local.workshopcode1004
local.workshoptitleStatistical Issues in Prediction: what can be learned for individualized predictive medicine?
local.organizersLeonhard Held, Zürich; Robin Henderson, Newcastle upon Tyne; Ulrich Mansmann, München
local.report-nameWorkshop Report 2010,6
local.opc-photo-id1004
local.publishers-doi10.4171/OWR/2010/06
local.ems-referenceHeld Leonhard, Henderson Robin, Mansmann Ulrich: Statistical Issues in Prediction: what can be learned for individualized predictive medicine?. Oberwolfach Rep. 7 (2010), 217-251. doi: 10.4171/OWR/2010/06


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