| 姚婷婷,刘媛媛,李长平,胡良平.生存资料回归模型分析——生存资料Cox比例风险回归模型分析[J].四川精神卫生杂志,2020,33(1):27-32.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 |
| 生存资料回归模型分析——生存资料Cox比例风险回归模型分析 |
| Analysis of regression model of survival data——analysis of Cox’s proportional hazards regression model of survival data |
| 投稿时间：2020-01-06 |
| DOI：10.11886/scjsws20200106003 |
| 中文关键词: PH假定 生存率曲线 回归分析 Cox比例风险回归模型 生存预测 |
| 英文关键词:PH assumption Survival curve Regression analysis Cox s proportional hazards regression model Survival prediction |
| 基金项目: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） |
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| 中文摘要: |
| 本文目的是介绍生存资料Cox比例风险回归模型分析的概念、作用及使用SAS软件实现计算的方法。首先介绍相关基本概念，包括“Cox比例风险回归模型简介”“模型假定及其检验”“参数解释”和“参数估计与假设检验”；然后通过一个实例并基于SAS软件演示如何实施生存资料Cox比例风险回归模型分析，内容包括“产生SAS数据集”“绘制生存曲线图”“判断PH假定是否成立”和“算出参数估计值与假设检验结果”。结果表明：当生存资料满足PH假定时，Cox比例风险回归模型可用于生存资料影响因素分析、校正混杂因素后的组间比较以及对每个个体进行预后指数和生存率的预测。 |
| 英文摘要: |
| 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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