Factors effecting the model performance measures area under the ROC curve,net reclassification improvement and integrated discrimination improvement |
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Authors: | Eda Karaismailoglu Naime Meric Konar Dincer Goksuluk Ahmet Ergun Karaagaoglu |
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Institution: | 1. Department of Biostatistics, Faculty of Medicine, Kastamonu University, Kuzeykent, Kastamonu, Turkeyekaraismailoglu@kastamonu.edu.tr;3. Department of Biostatistics, Faculty of Medicine, Hacettepe University, Sihhiye, Ankara, Turkey |
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Abstract: | ABSTRACTThe aim of this study is to investigate the impact of correlation structure, prevalence and effect size on the risk prediction model by using the change in the area under the receiver operating characteristic curve (ΔAUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). In simulation study, the dataset is generated under different correlation structures, prevalences and effect sizes. We verify the simulation results with the real-data application. In conclusion, the correlation structure between the variables should be taken into account while composing a multivariable model. Negative correlation structure between independent variables is more beneficial while constructing a model. |
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Keywords: | ΔAUC Correlation structure IDI NRI Risk prediction model |
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