协变量
比例危险模型
生存分析
统计
数学
非参数统计
统计的
对数秩检验
人口
反向
计量经济学
医学
几何学
环境卫生
作者
Stephen R. Cole,Miguel A. Hernán
标识
DOI:10.1016/j.cmpb.2003.10.004
摘要
Kaplan–Meier survival curves and the associated nonparametric log rank test statistic are methods of choice for unadjusted survival analyses, while the semiparametric Cox proportional hazards regression model is used ubiquitously as a method for covariate adjustment. The Cox model extends naturally to include covariates, but there is no generally accepted method to graphically depict adjusted survival curves. The authors describe a method and provide a simple worked example using inverse probability weights (IPW) to create adjusted survival curves. When the weights are non-parametrically estimated, this method is equivalent to direct standardization of the survival curves to the combined study population.
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