计算机科学
协变量
生物统计学
软件
计量经济学
估计
数据挖掘
统计模型
机器学习
数据科学
数学
工程类
程序设计语言
系统工程
医学
护理部
公共卫生
作者
Hein Putter,Marta Fiocco,Ronald B. Geskus
摘要
Abstract Standard survival data measure the time span from some time origin until the occurrence of one type of event. If several types of events occur, a model describing progression to each of these competing risks is needed. Multi‐state models generalize competing risks models by also describing transitions to intermediate events. Methods to analyze such models have been developed over the last two decades. Fortunately, most of the analyzes can be performed within the standard statistical packages, but may require some extra effort with respect to data preparation and programming. This tutorial aims to review statistical methods for the analysis of competing risks and multi‐state models. Although some conceptual issues are covered, the emphasis is on practical issues like data preparation, estimation of the effect of covariates, and estimation of cumulative incidence functions and state and transition probabilities. Examples of analysis with standard software are shown. Copyright © 2006 John Wiley & Sons, Ltd.
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