Factors effecting the model performance measures area under the ROC curve, net reclassification improvement and integrated discrimination improvement

Karaismailoglu E., Konar N. M. , Goksuluk D. , KARAAĞAOĞLU A. E.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.48, sa.9, ss.2586-2598, 2019 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 48 Konu: 9
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1080/03610918.2018.1458135
  • Sayfa Sayıları: ss.2586-2598


The 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 (Delta AUC), 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.