Concordance probability and discriminatory power in proportional hazards regression
By Mithat Gonen, G. Heller. 2005
721 citations recorded by the source corpus.
Subfields: Finance, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/450086eb400183aa694a8714d46b976b3b4f9b5c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
In Statistics and Probability
- Ewout W. Steyerberg
- Douglas G. Altman
- Karel G. M. Moons
- Patrick Royston
- Andrew J. Vickers
- Gary S. Collins
- Michael J. Pencina
- Nancy R. Cook
Citations in the corpus
- On the C-statistics for Evaluating Overall Adequacy of Risk Prediction Procedures with Censored Survival Data (2011, neutral): “Note that Gönen and Heller [17] proposed a method for censored survival data to estimate pr(T2>T1|g(Z1)>g(Z2)), which is also a concordance measure and has a similar form to (1), but we do not focus on this type of measures in this paper.”
- Assessing the performance of prediction models: a framework for some traditional and novel measures (2010, methodology): “Gonen and Heller have proposed a method to estimate a variant of the c statistic that is independent of censoring, but holds only in the context of a Cox proportional hazards model.(7) Furthermore, time-dependent c statistics have been proposed.”
- Prognostic Models With Competing Risks: Methods and Application to Coronary Risk Prediction (2009, background): “First, by conditioning on the events being observed, the c index depends on the censoring distribution.(33) This is a minor issue in our case study, in which all patients have a similar follow-up duration and loss to follow-up is minimal.”
- External validation of a Cox prognostic model: principles and methods (2013, methodology): “Here, for the purpose of illustration we focus on three measures: Harrell’s c-index of concordance [34], Gönen andHeller’s unbiased concordance statisticK [35], and the Royston-Sauerbrei D statistic [26].”
- Toward more realistic drug–target interaction predictions (2014, positive): “concordance index (CI) as an evaluation metric for the prediction accuracy [32].”
- A novel clinical risk prediction model for sudden cardiac death in hypertrophic cardiomyopathy (HCM risk-SCD). (2014, methodology): “Comparison with conventional risk factors Clinical practice guidelines consider severe hypertrophy (maximal wall thickness ≥30 mm), non-sustained ventricular tachycardia (NSVT), family history of SCD, and unexplained syncope as conventional risk factors of SCD.1,2 To compare the risk model developed”