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Journal of Health Informatics and Statistics10.21032/jhis.2022.47.s3.s51202247Suppl 3S51-S60Analyzing Survival Data with Competing Risks Based on R-packagesJinheum Kimhttp://e-jhis.org/upload/pdf/jhis-2022-47-S3-S51.pdf, http://e-jhis.org/journal/view.php?doi=10.21032/jhis.2022.47.S3.S51, http://e-jhis.org/upload/pdf/jhis-2022-47-S3-S51.pdf
Biometrics10.1111/j.1541-0420.2010.01470.x2010672415-426Frailty-Based Competing Risks Model for Multivariate Survival DataMalka Gorfine, Li Hsuhttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1541-0420.2010.01470.x, http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1541-0420.2010.01470.x/fullpdf
Statistics in Medicine10.1002/sim.35162009286956-971Simulating competing risks data in survival analysisJan Beyersmann, Aurélien Latouche, Anika Buchholz, Martin Schumacherhttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fsim.3516, https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fsim.3516, http://onlinelibrary.wiley.com/wol1/doi/10.1002/sim.3516/fullpdf
Biometrics10.1111/j.1541-0420.2005.00341.x2005613729-737A Semiparametric Mixture Model for Analyzing Clustered Competing Risks DataMalay Naskar, Kalyan Das, Joseph G. Ibrahimhttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1541-0420.2005.00341.x, http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1541-0420.2005.00341.x/fullpdf
Radiotherapy and Oncology10.1016/j.radonc.2018.09.0072019130185-189Competing risks in survival data analysisAlmut Dutz, Steffen Löckhttps://api.elsevier.com/content/article/PII:S016781401833490X?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S016781401833490X?httpAccept=text/plain
Lifetime Data Analysis10.1007/s10985-012-9221-92012183339-363Bayesian inference of the fully specified subdistribution model for survival data with competing risksMiaomiao Ge, Ming-Hui Chenhttp://link.springer.com/content/pdf/10.1007/s10985-012-9221-9.pdf, http://link.springer.com/article/10.1007/s10985-012-9221-9/fulltext.html, http://link.springer.com/content/pdf/10.1007/s10985-012-9221-9
Computer Methods and Programs in Biomedicine10.1016/j.cmpb.2018.03.0172018159185-198Tree-based models for survival data with competing risksMalgorzata Kretowskahttps://api.elsevier.com/content/article/PII:S0169260717314347?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S0169260717314347?httpAccept=text/plain
Lifetime Data Analysis10.1007/s10985-022-09576-22022Targeted maximum likelihood estimation for causal inference in survival and competing risks analysisHelene C. W. Rytgaard, Mark J. van der Laanhttps://link.springer.com/content/pdf/10.1007/s10985-022-09576-2.pdf, https://link.springer.com/article/10.1007/s10985-022-09576-2/fulltext.html, https://link.springer.com/content/pdf/10.1007/s10985-022-09576-2.pdf
Biometrical Journal10.1002/bimj.47103407071992347801-814Analysis of Survival Data with Two Dependent Competing RisksIsha Bagai, B. L. S. Prakasa Raohttps://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fbimj.4710340707, https://onlinelibrary.wiley.com/doi/full/10.1002/bimj.4710340707
Lifetime Data Analysis10.1007/s10985-006-9015-z2006123285-303Bounds on the covariate-time transformation for competing-risks survival analysisSimon J. Bond, J. Ewart H. Shawhttp://link.springer.com/content/pdf/10.1007/s10985-006-9015-z.pdf, http://link.springer.com/article/10.1007/s10985-006-9015-z/fulltext.html, http://link.springer.com/content/pdf/10.1007/s10985-006-9015-z