Prediction Accuracy Measures for a Nonlinear Model and for Right-Censored Time-to-Event Data.

ABSTRACT: This article develops a pair of new prediction summary measures for a nonlinear prediction function with right-censored time-to-event data. The first measure, defined as the proportion of explained variance by a linearly corrected prediction function, quantifies the potential predictive power of the nonlinear prediction function. The second measure, defined as the proportion of explained prediction error by its corrected prediction function, gauges the closeness of the prediction function to its corrected version and serves as a supplementary measure to indicate (by a value less than 1) whether the correction is needed to fulfill its potential predictive power and quantify how much prediction error reduction can be realized with the correction. The two measures together provide a complete

SUBMITTER: Li G 

PROVIDER: S-EPMC7454169 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature