Optimal cutpoint estimation with censored data Journal Article


Authors: Sima, C. S.; Gonen, M.
Article Title: Optimal cutpoint estimation with censored data
Abstract: Maximal chi-squared methods and receiver operating characteristic (ROC) curves-based methods are commonly used to dichotomize a continous predictor when the outcome is binary. In this article we consider this problem when the outcome of interest is subject to right censoring, with a twofold goal. First, we propose maximal concordance, a measure similar to the area under an ROC curve, as a metric for selecting an optimal cutpoint with censored endpoints. To support this, we show that selecting the cutpoint that maximizes the concordance probability is equivalent to maximizing the Youden index, a popular criterion when the ROC curve is used to choose a threshold with binary outcomes. Second, we compare the performance of two concordance-based metrics (c-index and concordance probability estimate) and the performance of three chi-squared-based metrics (Wald, log-rank, and partial likelihood ratio statistics). In our simulations performed under a variety of assumptions, maximizing the partial likelihood ratio test statistic has the best performance. © 2013 Copyright Grace Scientific Publishing, LLC.
Keywords: survival; roc curve; threshold; concordance; maximal chi-squared
Journal Title: Journal of Statistical Theory and Practice
Volume: 7
Issue: 2
ISSN: 1559-8608
Publisher: Taylor & Francis Group  
Date Published: 2013-01-01
Start Page: 345
End Page: 359
Language: English
PROVIDER: scopus
DOI: 10.1080/15598608.2013.772022
DOI/URL:
Notes: --- - "Export Date: 1 May 2013" - ":doi 10.1080/15598608.2013.772022" - "Source: Scopus"
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  1. Camelia S Sima
    212 Sima
  2. Mithat Gonen
    1030 Gonen