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Analysis of Censored Survival Data with Dimension Reduction Methods: Tehran Lipid and Glucose Study
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Azam Rastin   , Mohmmadreza Faridrohani , Amirabbas Momenan , Fatemeh Eskandari , Davood Khalili * |
| Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, |
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Abstract: (3596 Views) |
Cardiovascular diseases (CVDs) are the leading cause of death worldwide. To specify an appropriate model to determine the risk of CVD and predict survival rate, users are required to specify a functional form which relates the outcome variables to the input ones. In this paper, we proposed a dimension reduction method using a general model, which includes many widely used survival models as special cases.
Using an appropriate combination of dimension reduction and Cox Proportional Hazards model, we found a method which is effective for survival prediction. |
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| Keywords: Cardiovascular disease, prediction models, sufficient dimension reduction, inverse regression. |
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Full-Text [PDF 259 kb]
(1209 Downloads)
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Type of Study: Research |
Subject:
General
Received: 2018/03/9 | Accepted: 2019/02/28 | Published: 2019/04/25
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