| Abstract: |
The continuous net reclassification improvement (NRI) statistic is a popular model change measure that was developed to assess the incremental value of new factors in a risk prediction model. Two prominent statistical issues identified in the literature call the utility of this measure into question: (1) it is not a proper scoring function and (2) it has a high false positive rate when testing whether new factors contribute to the risk model. For binary response regression models, these subjects are interrogated and a modification of the continuous NRI, guided by the likelihood-based score residual, is proposed to address these issues. Within a nested model framework, the modified NRI may be viewed as a distance measure between two risk models. An application of the modified NRI is illustrated using prostate cancer data. © 2023 Elsevier B.V. |
