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Statistics in Medicine
Article . 2006 . Peer-reviewed
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Tutorial in biostatistics: competing risks and multi‐state models

Authors: Putter, H.; Fiocco, M.; Geskus, R. B.;

Tutorial in biostatistics: competing risks and multi‐state models

Abstract

AbstractStandard 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.

Related Organizations
Keywords

Biometry, Models, Statistical, Humans, HIV Infections, Risk Assessment, Survival Analysis, Netherlands

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2K
Top 0.01%
Top 0.1%
Top 1%
bronze