Estimation of the false negative fraction of a diagnostic kit through Bayesian regression model averaging

In modelling we usually endeavour to find a single ‘best’ model that explains the relationship between independent and dependent variables. Selection of a single model fails to take into account the prior uncertainty in the model space. The Bayesian model averaging (BMA) approach tackles this proble...

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Veröffentlicht in:	Statistics in medicine 2006-02, Vol.25 (4), p.653-667
Hauptverfasser:	Ranyimbo, A. O., Held, L.
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes Theorem Bayesian analysis Bayesian model averaging Data Interpretation, Statistical false negative fraction False Negative Reactions Feces Intestinal Neoplasms - diagnosis Mass Screening Medical diagnosis Models, Statistical Reagent Kits, Diagnostic Regression analysis screening selection Sigmoidoscopy
Online-Zugang:	Volltext
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