摘要
Ｃｏｘ比例危险回归模型是医学随访研究、临床试验研究中分析生存资料最常用的多因素分析方法，但它不适合于处理分组生存资料或重叠严重的大样本生存数据。笔者对分组比例危险回归模型及其在大样本寿命表生存资料分析中的应用进行了讨论。最后结合实例借助于ＧＬＩＭ软件探讨它在肺癌随访资料预后因素分析中的应用。
ox proportional hazards regression modelis the most popular multivariate regression model for analysis of survival data in medical follow-up studies and clinical trials,but it is unable to handle grouped survival data or-large data sets with many tied failure times adequately. This paper explores the grouped proportional hazards regression model(GPH model)and its use in analysis of large data sets presented in life tables.By use of the data in a lung cancer follow-up study conducted in urban area of Shanghai,the au-thors give an example in detail for analysing piognostic factors of lung cancer by using GLIM.
出处
《中华流行病学杂志》
CAS
CSCD
北大核心
1994年第1期46-50,共5页
Chinese Journal of Epidemiology
关键词
分组Cox模型
癌
肺肿瘤
预后
roportional hazards regres-sion model Grouped Cox model GLM Lung cancer
