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Erschienen in: Journal of Nuclear Cardiology 6/2017

01.12.2017 | Original Article

Quantifying predictive accuracy in survival models

verfasst von: Seth T. Lirette, MS, Inmaculada Aban, PhD

Erschienen in: Journal of Nuclear Cardiology | Ausgabe 6/2017

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Abstract

For time-to-event outcomes in medical research, survival models are the most appropriate to use. Unlike logistic regression models, quantifying the predictive accuracy of these models is not a trivial task. We present the classes of concordance (C) statistics and R 2 statistics often used to assess the predictive ability of these models. The discussion focuses on Harrell’s C, Kent and O’Quigley’s R 2, and Royston and Sauerbrei’s R 2. We present similarities and differences between the statistics, discuss the software options from the most widely used statistical analysis packages, and give a practical example using the Worcester Heart Attack Study dataset.
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Metadaten
Titel
Quantifying predictive accuracy in survival models
verfasst von
Seth T. Lirette, MS
Inmaculada Aban, PhD
Publikationsdatum
01.12.2017
Verlag
Springer US
Erschienen in
Journal of Nuclear Cardiology / Ausgabe 6/2017
Print ISSN: 1071-3581
Elektronische ISSN: 1532-6551
DOI
https://doi.org/10.1007/s12350-015-0296-z

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