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October 10, 2006Statistics in Medicine2,471 citations

Tutorial in biostatistics: competing risks and multi‐state models

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HPHein PutterMFMarta FioccoRGRonald B. Geskus

Key Points

  • The tutorial aims to review methods for analyzing competing risks and multi-state models in statistical contexts.
  • Review of statistical methods for competing risks and multi-state models.
  • Emphasis on data preparation and programming with standard statistical packages.
  • Estimation of covariate effects, cumulative incidence functions, and transition probabilities.
  • Practical analysis examples using standard software are provided.
  • Conceptual issues in the models are discussed alongside practical applications.

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.

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Cite This Study

Putter et al. (2006) studied this question.

synapsesocial.com/papers/69d83a4852654bb436d18b29https://doi.org/10.1002/sim.2712
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