On the optimism correction of the area under the receiver operating characteristic curve in logistic prediction models
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...
| Authors: | , , |
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| Format: | article |
| Publication Date: | 2019 |
| Country: | España |
| Institution: | Universitat Autònoma de Barcelona |
| Repository: | Dipòsit Digital de Documents de la UAB |
| Language: | English |
| OAI Identifier: | oai:ddd.uab.cat:205824 |
| Online Access: | https://ddd.uab.cat/record/205824 https://dx.doi.org/urn:doi:10.2436/20.8080.02.82 |
| Access Level: | Open access |
| Keyword: | Prediction models Logistic regression Area under the receiver operating characteristic curve Validation Bootstrap |
| Summary: | 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. |
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