A Proper Scoring Rule for Validation of Competing Risks Models
Methodology
2021-04-05 v1
Abstract
Scoring rules are used to evaluate the quality of predictions that take the form of probability distributions. A scoring rule is strictly proper if its expected value is uniquely minimized by the true probability distribution. One of the most well-known and widely used strictly proper scoring rules is the logarithmic scoring rule. We propose a version of the logarithmic scoring rule for competing risks data and show that it remains strictly proper under non-informative censoring.
Keywords
Cite
@article{arxiv.2104.01000,
title = {A Proper Scoring Rule for Validation of Competing Risks Models},
author = {Zoe Guan},
journal= {arXiv preprint arXiv:2104.01000},
year = {2021}
}