医学
生存分析
肾病科
事件(粒子物理)
比例危险模型
重症监护医学
内科学
结果(博弈论)
介绍(产科)
事件数据
外科
统计
物理
数理经济学
协变量
量子力学
数学
作者
Vianda S Stel,Friedo W. Dekker,Giovanni Tripepi,Carmine Zoccali,Kitty J. Jager
出处
期刊:Nephron
[S. Karger AG]
日期:2011-06-15
卷期号:119 (1): c83-c88
被引量:131
摘要
The Kaplan-Meier (KM) method is used to analyze ‘time-to-event’ data. The outcome in KM analysis often includes all-cause mortality, but could also include other outcomes such as the occurrence of a cardiovascular event. The purpose of this article is to explain the basic concepts of the KM method, to provide some guidance regarding the presentation of the KM results and to discuss some important limitations of this method. To do this, we use a clinical example derived from the nephrology literature.
科研通智能强力驱动
Strongly Powered by AbleSci AI