Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer

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Standard

Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer. / Klein, John P.; Keiding, Niels; Kamby, Claus.

I: Biometrics, Bind 45, Nr. 4, 12.1989, s. 1073-1086.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Klein, JP, Keiding, N & Kamby, C 1989, 'Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer', Biometrics, bind 45, nr. 4, s. 1073-1086. https://doi.org/10.2307/2531761

APA

Klein, J. P., Keiding, N., & Kamby, C. (1989). Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer. Biometrics, 45(4), 1073-1086. https://doi.org/10.2307/2531761

Vancouver

Klein JP, Keiding N, Kamby C. Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer. Biometrics. 1989 dec.;45(4):1073-1086. https://doi.org/10.2307/2531761

Author

Klein, John P. ; Keiding, Niels ; Kamby, Claus. / Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer. I: Biometrics. 1989 ; Bind 45, Nr. 4. s. 1073-1086.

Bibtex

@article{e2afbac8cf444fc5b559836fb6dc5de9,
title = "Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer",
abstract = "It is noted that the bivariate exponential distribution introduced by Marshall and Olkin (1967, Journal of the American Statistical Association 62, 30-40) allows semiparametric generalizations along the lines of the Cox regression model for survival data. Partial likelihoods for the regression parameters may be derived (here illustrated by the use of the profile likelihood construction), and in most cases standard Cox regression model software may be applied for the analysis with minor modification of the input files. The study was initiated by data on occurrence of metastases from breast cancer. Metastases may occur at various sites, here grouped into ten categories, and simultaneous as well as consecutive occurrence at several sites in common. It is desired to identify and compare risk factors for development of metastases at each site, and we illustrate on some of these data that the above models may be useful for this purpose.",
author = "Klein, {John P.} and Niels Keiding and Claus Kamby",
year = "1989",
month = dec,
doi = "10.2307/2531761",
language = "English",
volume = "45",
pages = "1073--1086",
journal = "Biometrics",
issn = "0006-341X",
publisher = "Wiley-Blackwell",
number = "4",

}

RIS

TY - JOUR

T1 - Semiparametric Marshall-Olkin models applied to the occurrence of metastases at multiple sites after breast cancer

AU - Klein, John P.

AU - Keiding, Niels

AU - Kamby, Claus

PY - 1989/12

Y1 - 1989/12

N2 - It is noted that the bivariate exponential distribution introduced by Marshall and Olkin (1967, Journal of the American Statistical Association 62, 30-40) allows semiparametric generalizations along the lines of the Cox regression model for survival data. Partial likelihoods for the regression parameters may be derived (here illustrated by the use of the profile likelihood construction), and in most cases standard Cox regression model software may be applied for the analysis with minor modification of the input files. The study was initiated by data on occurrence of metastases from breast cancer. Metastases may occur at various sites, here grouped into ten categories, and simultaneous as well as consecutive occurrence at several sites in common. It is desired to identify and compare risk factors for development of metastases at each site, and we illustrate on some of these data that the above models may be useful for this purpose.

AB - It is noted that the bivariate exponential distribution introduced by Marshall and Olkin (1967, Journal of the American Statistical Association 62, 30-40) allows semiparametric generalizations along the lines of the Cox regression model for survival data. Partial likelihoods for the regression parameters may be derived (here illustrated by the use of the profile likelihood construction), and in most cases standard Cox regression model software may be applied for the analysis with minor modification of the input files. The study was initiated by data on occurrence of metastases from breast cancer. Metastases may occur at various sites, here grouped into ten categories, and simultaneous as well as consecutive occurrence at several sites in common. It is desired to identify and compare risk factors for development of metastases at each site, and we illustrate on some of these data that the above models may be useful for this purpose.

UR - http://www.scopus.com/inward/record.url?scp=0024913271&partnerID=8YFLogxK

U2 - 10.2307/2531761

DO - 10.2307/2531761

M3 - Journal article

C2 - 2611318

AN - SCOPUS:0024913271

VL - 45

SP - 1073

EP - 1086

JO - Biometrics

JF - Biometrics

SN - 0006-341X

IS - 4

ER -

ID: 202081348