Tutorial in biostatistics: competing risks and multi‐state models
Top Cited Papers
- 10 October 2006
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 26 (11) , 2389-2430
- https://doi.org/10.1002/sim.2712
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.Keywords
This publication has 46 references indexed in Scilit:
- Reduced rank proportional hazards model for competing risks: An application to a breast cancer trialJournal of Statistical Planning and Inference, 2005
- Reduced rank proportional hazards model for competing risksBiostatistics, 2005
- Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence FunctionBiometrics, 2005
- Generalised linear models for correlated pseudo-observations, with applications to multi-state modelsBiometrika, 2003
- On the issue of ‘multiple’ first failures in competing risks analysisStatistics in Medicine, 2002
- A Proportional Hazards Model for the Subdistribution of a Competing RiskJournal of the American Statistical Association, 1999
- Cox Regression in a Markov Renewal Model: An Application to the Analysis of Bone Marrow Transplant DataJournal of the American Statistical Association, 1994
- Semiparametric analysis of the additive risk modelBiometrika, 1994
- A Class of $K$-Sample Tests for Comparing the Cumulative Incidence of a Competing RiskThe Annals of Statistics, 1988
- Semi-Markov models for partially censored dataBiometrika, 1978