survcomp: An R/Bioconductor package for performance assessment and comparison of survival models

Markus S. Schröder; Aedín C. Culhane; John Quackenbush; Benjamin Haibe-Kains

doi:10.1093/bioinformatics/btr511

survcomp: An R/Bioconductor package for performance assessment and comparison of survival models

Markus S. Schröder, Aedín C. Culhane, John Quackenbush, Benjamin Haibe-Kains

Dana-Farber Cancer Institute

Research output: Contribution to journal › Article › peer-review

Abstract

Summary: The survcomp package provides functions to assess and statistically compare the performance of survival/risk prediction models. It implements state-of-the-art statistics to (i) measure the performance of risk prediction models; (ii) combine these statistical estimates from multiple datasets using a meta-analytical framework; and (iii) statistically compare the performance of competitive models.

Original language	English
Article number	btr511
Pages (from-to)	3206-3208
Number of pages	3
Journal	Bioinformatics
Volume	27
Issue number	22
DOIs	https://doi.org/10.1093/bioinformatics/btr511
Publication status	Published - Nov 2011
Externally published	Yes

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10.1093/bioinformatics/btr511

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title = "survcomp: An R/Bioconductor package for performance assessment and comparison of survival models",

abstract = "Summary: The survcomp package provides functions to assess and statistically compare the performance of survival/risk prediction models. It implements state-of-the-art statistics to (i) measure the performance of risk prediction models; (ii) combine these statistical estimates from multiple datasets using a meta-analytical framework; and (iii) statistically compare the performance of competitive models.",

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AU - Quackenbush, John

AU - Haibe-Kains, Benjamin

PY - 2011/11

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AB - Summary: The survcomp package provides functions to assess and statistically compare the performance of survival/risk prediction models. It implements state-of-the-art statistics to (i) measure the performance of risk prediction models; (ii) combine these statistical estimates from multiple datasets using a meta-analytical framework; and (iii) statistically compare the performance of competitive models.

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JO - Bioinformatics

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survcomp: An R/Bioconductor package for performance assessment and comparison of survival models

Abstract

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