Universitat Autònoma de Barcelona
When the same data are used to fit a model and estimate its predictive performance, this estimate may be optimistic, and its correction is required. The aim of this work is to compare the behaviour of different methods proposed in the literature when correcting for the optimism of the estimated area under the receiver operating characteristic curve in logistic regression models. A simulation study (where the theoretical model is known) is conducted considering different number of covariates, sample size, prevalence and correlation among covariates. The results suggest the use of k-fold cross-validation with replication and bootstrap.
English
Prediction models; Logistic regression; Area under the receiver operating characteristic curve; Validation; Bootstrap
;
SORT : statistics and operations research transactions ; Vol. 43 Núm. 1 (January-June 2019), p. 145-162
open access
Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
https://creativecommons.org/licenses/by-nc-nd/4.0/
