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Survival analyses with dependent covariates: A regression tree-base approach | ||
| Journal of Algorithms and Computation | ||
| دوره 52، شماره 1، شهریور 2020، صفحه 105-129 اصل مقاله (874.6 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jac.2020.76520 | ||
| نویسندگان | ||
| Mostafa Boskabadi1؛ Mahdi Doostparast* 2؛ Majid Sarmad1 | ||
| 1Department of Statistics‎, ‎Ferdowsi University of Mashhad‎, ‎P.O‎. ‎Box 91775-1159‎, ‎Khorasan Razavi‎, ‎Iran | ||
| 2Department of Statistics, School of Mathematical Sciences, Ferdowsi University of Mashhad | ||
| چکیده | ||
| Cox proportional hazards models are the most common modelling framework to prediction and evaluation of covariate effects in time-to-event analyses. These models usually do not account the relationship among covariates which may have impacts on survival times. In this article, we introduce regression tree models for survival analyses by incorporating dependencies among covariates. Various properties of the proposed model are studied in details. To assess the accuracy of the proposed model, a Monte--Carlo simulation study is conducted. A real data set from assay of serum free light chain is also analysed to illustrate advantages of the proposed method in medical investigations. | ||
| کلیدواژه‌ها | ||
| Survival tree؛ Cox proportional hazards model؛ Dependence؛ Copula function | ||
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آمار تعداد مشاهده مقاله: 282 تعداد دریافت فایل اصل مقاله: 321 |
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