Results 301 to 310 of about 1,167,728 (343)
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2016
In the previous chapters we considered various statistical techniques that model the time to a particular event of interest. In this chapter, we consider competing risks models, which extend the previously described models to survival data with several distinct types of target events.
Gerhard Tutz, Matthias Schmid
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In the previous chapters we considered various statistical techniques that model the time to a particular event of interest. In this chapter, we consider competing risks models, which extend the previously described models to survival data with several distinct types of target events.
Gerhard Tutz, Matthias Schmid
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Identifiability Crises in Competing Risks
International Statistical Review / Revue Internationale de Statistique, 1994Summary: Difficulties and pitfalls of dependency modelling in Statistics are very well illustrated by problems of identifiability in Competing Risks. This paper gives a review of such problems with examples intended to animate the theoretical results. The problems covered arise through the traditional way of modelling Competing Risks via latent failure
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2000
The term competing risks refers to cause of death models. Competing risks have been introduced and illustrated as a multi-state model in Figure 1.7 and discussed previously, in Sections 1.10, 3.3.9, and Chapter 5; but such data present special challenges, and therefore are considered separately in this chapter.
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The term competing risks refers to cause of death models. Competing risks have been introduced and illustrated as a multi-state model in Figure 1.7 and discussed previously, in Sections 1.10, 3.3.9, and Chapter 5; but such data present special challenges, and therefore are considered separately in this chapter.
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1988
Competing risk theory hypothesizes k risks (diseases, accidents, etc.) which compete for the lives of individuals. For each individual, one of these risks will ‘win,’ and the individual will die from that risk. The theory then attempts to predict the consequence of removing or adding a risk. For example, what would be the effect on life expectancy if a
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Competing risk theory hypothesizes k risks (diseases, accidents, etc.) which compete for the lives of individuals. For each individual, one of these risks will ‘win,’ and the individual will die from that risk. The theory then attempts to predict the consequence of removing or adding a risk. For example, what would be the effect on life expectancy if a
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Compartmental models and competing risk
Mathematical Biosciences, 1994General compartmental models are derived using competing risk arguments. When the risk variables are exponential, the results specialize to the standard stationary Markov compartmental model. Iterative methods of solving the fundamental integral equation are given, and the uniqueness of the solution is incidentally established. The analysis is extended
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Survival Analysis with Competing Risks and Semi-competing Risks Data
2017Competing risks data arise when study subjects are subject to multiple types of failure events. The competing risks events are terminating, in that the onset of one event precludes the observation of other events. Semi-competing risks data involve a nonterminating event and a terminating event.
Ruosha Li, Limin Peng
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