Random survival forests for competing risks

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Standard

Random survival forests for competing risks. / Ishwaran, Hemant; Gerds, Thomas A; Kogalur, Udaya B; Moore, Richard D; Gange, Stephen J; Lau, Bryan M.

I: Biostatistics, Bind 15, Nr. 4, 2014, s. 757-73.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Ishwaran, H, Gerds, TA, Kogalur, UB, Moore, RD, Gange, SJ & Lau, BM 2014, 'Random survival forests for competing risks', Biostatistics, bind 15, nr. 4, s. 757-73. https://doi.org/10.1093/biostatistics/kxu010

APA

Ishwaran, H., Gerds, T. A., Kogalur, U. B., Moore, R. D., Gange, S. J., & Lau, B. M. (2014). Random survival forests for competing risks. Biostatistics, 15(4), 757-73. https://doi.org/10.1093/biostatistics/kxu010

Vancouver

Ishwaran H, Gerds TA, Kogalur UB, Moore RD, Gange SJ, Lau BM. Random survival forests for competing risks. Biostatistics. 2014;15(4):757-73. https://doi.org/10.1093/biostatistics/kxu010

Author

Ishwaran, Hemant ; Gerds, Thomas A ; Kogalur, Udaya B ; Moore, Richard D ; Gange, Stephen J ; Lau, Bryan M. / Random survival forests for competing risks. I: Biostatistics. 2014 ; Bind 15, Nr. 4. s. 757-73.

Bibtex

@article{2cbe3ed1a854455089993c454907b11d,

title = "Random survival forests for competing risks",

abstract = "We introduce a new approach to competing risks using random forests. Our method is fully non-parametric and can be used for selecting event-specific variables and for estimating the cumulative incidence function. We show that the method is highly effective for both prediction and variable selection in high-dimensional problems and in settings such as HIV/AIDS that involve many competing risks.",

author = "Hemant Ishwaran and Gerds, {Thomas A} and Kogalur, {Udaya B} and Moore, {Richard D} and Gange, {Stephen J} and Lau, {Bryan M}",

year = "2014",

doi = "10.1093/biostatistics/kxu010",

language = "English",

volume = "15",

pages = "757--73",

journal = "Biostatistics",

issn = "1465-4644",

publisher = "Oxford University Press",

number = "4",

}

RIS

TY - JOUR

T1 - Random survival forests for competing risks

AU - Ishwaran, Hemant

AU - Gerds, Thomas A

AU - Kogalur, Udaya B

AU - Moore, Richard D

AU - Gange, Stephen J

AU - Lau, Bryan M

PY - 2014

Y1 - 2014

N2 - We introduce a new approach to competing risks using random forests. Our method is fully non-parametric and can be used for selecting event-specific variables and for estimating the cumulative incidence function. We show that the method is highly effective for both prediction and variable selection in high-dimensional problems and in settings such as HIV/AIDS that involve many competing risks.

AB - We introduce a new approach to competing risks using random forests. Our method is fully non-parametric and can be used for selecting event-specific variables and for estimating the cumulative incidence function. We show that the method is highly effective for both prediction and variable selection in high-dimensional problems and in settings such as HIV/AIDS that involve many competing risks.

U2 - 10.1093/biostatistics/kxu010

DO - 10.1093/biostatistics/kxu010

M3 - Journal article

C2 - 24728979

VL - 15

SP - 757

EP - 773

JO - Biostatistics

JF - Biostatistics

SN - 1465-4644

IS - 4

ER -

ID: 134780949