| Yao Tingting,Liu Yuanyuan,Li Changping,Hu Liangping,Analysis of regression model of survival data——analysis of Cox’s proportional hazards regression model of survival data[J].SICHUAN MENTAL HEALTH,2020,33(1):27-32 |
| Analysis of regression model of survival data——analysis of Cox’s proportional hazards regression model of survival data |
DOI：10.11886/scjsws20200106003 |
| English keywords:PH assumption Survival curve Regression analysis Cox s proportional hazards regression model Survival prediction |
| Fund projects:国家自然科学基金项目（项目名称：贝叶斯生存分析方法在肝细胞癌肝移植患者预后预测中的应用研究，项目编号：81803333） |
| Author Name | Affiliation | Postcode | | Yao Tingting | School of Public Health, Tianjin Medical University, Tianjin 300070, China | 300070 | | Liu Yuanyuan | School of Public Health, Tianjin Medical University, Tianjin 300070, China | 300070 | | Li Changping | School of Public Health, Tianjin Medical University, Tianjin 300070, China
Specialty Committee of Clinical Scientific Research Statistics of World Federation of Chinese Medicine Societies, Beijing 100029, China | 100029 | | Hu Liangping | Specialty Committee of Clinical Scientific Research Statistics of World Federation of Chinese Medicine Societies, Beijing 100029, China
Graduate School, Academy of Military Sciences PLA China, Beijing 100850, China | 100850 |
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| English abstract: |
| The purpose of this paper was to introduce the concepts and functions and the calculation methods of the Cox’s proportional hazards regression model analysis of survival data by using the SAS software. Firstly, the basic concepts of the regression analysis was introduced, including "introduction to Cox s proportional hazards regression model" "model assumption and tests" "parameter interpretation" and "parameter estimation and hypothesis testing", and then the Cox s proportional hazards regression model analysis was demonstrated through one example by using the SAS software, including "generating SAS data set" "drawing survival curve" "diagnosing whether PH hypothesis to be true" and "calculating parameter estimates and the results of hypothesis testing". The results showed that it could be used for the analysis of influencing factors of survival data, inter-group comparison after correction of confounding factors, and the prediction of prognostic index and survival rate for each individual in the survival data set which met the PH assumption by applying the Cox s proportional hazards regression model. |
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