Title: Updating and Calibration of Multinomial Risk Prediction Models
Other Titles: Updating en calibratie van multinomiale risico-predictiemodellen
Authors: Van Hoorde, Kirsten
Issue Date: 19-Dec-2014
Abstract: Risk prediction models for diagnostic or prognostic outcomes are useful tools for clinical decision support. Most commonly, a dichotomous outcome (e.g. a benign or malignant tumor) is considered. Especially in diagnostic problems, however, a differential diagnosis often includes more levels than categorization of subjects as ‘diseased’ versus ‘non-diseased’ (e.g. a benign, borderline or invasive tumor). Methods for updating existing risk prediction models, i.e. adjusting an existing model in order to improve predictions from future patients in a new and different setting, had already been suggested for dichotomous models but did not yet exist for multinomial models. Closely related, the aspect of calibration of multinomial risk prediction models, i.e. the reliability of the predicted risks, had not been studied extensively. Therefore, in this dissertation we extended calibration statistics, calibration plots as well as updating techniques to prediction models for polytomous outcomes based on multinomial logistic regression.
Publication status: published
KU Leuven publication type: TH
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Organ Systems (+)

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