[Roaming through methodology. XXXIV. Limitations of predictive models].
Predictive models can be readily used within the populations in which they were developed but they often give a less than satisfactory performance when applied to another population. The main cause of this poorer performance is the fact that predictive models are often developed and evaluated within one single population. In a lot of cases, the model includes too many predictors (or a small population is used), which increases the chance of overfitting. Both external and internal validation techniques have been developed to evaluate predictive models. The most stringent test is an external validation: the application of the model to a new population. The usability of a predictive model can be evaluated using the receiver operating characteristic (ROC) curve.
Visser
M
M
Vrije Universiteit, faculteit der Geneeskunde, Instituut voor Extramuraal Geneeskundig Onderzoek (EMGO-Instituut), Van der Boechorststraat 7, 1081 BT Amsterdam. m.visser.emgo@med.vu.nl
D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D012372:ROC Curve; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards*