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Eda Karaismailoglu Naime Meric Konar Dincer Goksuluk Ahmet Ergun Karaagaoglu 《统计学通讯:模拟与计算》2013,42(9):2586-2598
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. 相似文献
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