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stacov.bib
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stacov.bib
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@article{Diamond2013,
author = {Diamond, Alexis and Sekhon, Jasjeet S},
issn = {0034-6535},
journal = {Review of Economics and Statistics},
number = {3},
pages = {932--945},
publisher = {MIT Press},
title = {{Genetic matching for estimating causal effects: A general multivariate matching method for achieving balance in observational studies}},
volume = {95},
year = {2013}
}
@article{Tibshirani1996,
author = {Tibshirani, Robert},
issn = {0035-9246},
journal = {Journal of the Royal Statistical Society: Series B (Methodological)},
number = {1},
pages = {267--288},
publisher = {Wiley Online Library},
title = {{Regression shrinkage and selection via the lasso}},
volume = {58},
year = {1996}
}
@article{Latouche2013,
abstract = {Competing risks endpoints are frequently encountered in hematopoietic stem cell transplantation where patients are exposed to relapse and treatment-related mortality. Both cause-specific hazards and direct models for the cumulative incidence functions have been used for analyzing such competing risks endpoints. For both approaches, the popular models are of a proportional hazards type. Such models have been used for studying prognostic factors in acute and chronic leukemias. We argue that a complete understanding of the event dynamics requires that both hazards and cumulative incidence be analyzed side by side, and that this is generally the most rigorous scientific approach to analyzing competing risks data. That is, understanding the effects of covariates on cause-specific hazards and cumulative incidence functions go hand in hand. A case study illustrates our proposal.},
author = {Latouche, Aurelien and Allignol, Arthur and Beyersmann, Jan and Labopin, Myriam and Fine, Jason P},
doi = {10.1016/j.jclinepi.2012.09.017},
issn = {1878-5921 (Electronic)},
journal = {Journal of clinical epidemiology},
keywords = {Data Interpretation, Statistical,Hematopoietic Stem Cell Transplantation,Humans,Incidence,Models, Statistical,Recurrence,Risk Assessment,Survival Analysis,Time Factors,Transplantation Conditioning,Treatment Failure,mortality,statistics {\&} numerical data},
language = {eng},
month = {jun},
number = {6},
pages = {648--653},
pmid = {23415868},
title = {{A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions.}},
volume = {66},
year = {2013}
}
@article{Lau2009,
abstract = {Competing events can preclude the event of interest from occurring in epidemiologic data and can be analyzed by using extensions of survival analysis methods. In this paper, the authors outline 3 regression approaches for estimating 2 key quantities in competing risks analysis: the cause-specific relative hazard (csRH) and the subdistribution relative hazard (sdRH). They compare and contrast the structure of the risk sets and the interpretation of parameters obtained with these methods. They also demonstrate the use of these methods with data from the Women's Interagency HIV Study established in 1993, treating time to initiation of highly active antiretroviral therapy or to clinical disease progression as competing events. In our example, women with an injection drug use history were less likely than those without a history of injection drug use to initiate therapy prior to progression to acquired immunodeficiency syndrome or death by both measures of association (csRH = 0.67, 95{\%} confidence interval: 0.57, 0.80 and sdRH = 0.60, 95{\%} confidence interval: 0.50, 0.71). Moreover, the relative hazards for disease progression prior to treatment were elevated (csRH = 1.71, 95{\%} confidence interval: 1.37, 2.13 and sdRH = 2.01, 95{\%} confidence interval: 1.62, 2.51). Methods for competing risks should be used by epidemiologists, with the choice of method guided by the scientific question.},
author = {Lau, Bryan and Cole, Stephen R and Gange, Stephen J},
doi = {10.1093/aje/kwp107},
issn = {0002-9262},
journal = {American Journal of Epidemiology},
month = {jun},
number = {2},
pages = {244--256},
title = {{Competing Risk Regression Models for Epidemiologic Data}},
url = {https://doi.org/10.1093/aje/kwp107},
volume = {170},
year = {2009}
}
@article{Fine1999,
annote = {doi: 10.1080/01621459.1999.10474144},
author = {Fine, Jason P and Gray, Robert J},
doi = {10.1080/01621459.1999.10474144},
issn = {0162-1459},
journal = {Journal of the American Statistical Association},
month = {jun},
number = {446},
pages = {496--509},
publisher = {Taylor {\&} Francis},
title = {{A Proportional Hazards Model for the Subdistribution of a Competing Risk}},
url = {https://amstat.tandfonline.com/doi/abs/10.1080/01621459.1999.10474144},
volume = {94},
year = {1999}
}
@misc{Therneau2015,
author = {Therneau, Terry M and Crowson, Cynthia S and Atkinson, Elizabeth J},
publisher = {January},
title = {{Adjusted survival curves}},
year = {2015}
}