期刊名称：SORT-Statistics and Operations Research Transactions
印刷版ISSN：2013-8830
出版年度：2019
卷号：1
期号：1
页码：145-162
DOI：10.2436/20.8080.02.82
出版社：SORT- Statistics and Operations Research Transactions
摘要：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.
关键词：Prediction models ; logistic regression ; area under the receiver operating characteristic curve ; validation ; bootstrap
