Competing risks models and time-dependent covariates
- PMID: 18423067
- PMCID: PMC2447577
- DOI: 10.1186/cc6840
Competing risks models and time-dependent covariates
Abstract
New statistical models for analysing survival data in an intensive care unit context have recently been developed. Two models that offer significant advantages over standard survival analyses are competing risks models and multistate models. Wolkewitz and colleagues used a competing risks model to examine survival times for nosocomial pneumonia and mortality. Their model was able to incorporate time-dependent covariates and so examine how risk factors that changed with time affected the chances of infection or death. We briefly explain how an alternative modelling technique (using logistic regression) can more fully exploit time-dependent covariates for this type of data.
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Comment in
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Regression modelling in hospital epidemiology: a statistical note.Crit Care. 2008;12(5):427. doi: 10.1186/cc6991. Epub 2008 Sep 4. Crit Care. 2008. PMID: 18828871 Free PMC article. No abstract available.
Comment on
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Risk factors for the development of nosocomial pneumonia and mortality on intensive care units: application of competing risks models.Crit Care. 2008;12(2):R44. doi: 10.1186/cc6852. Epub 2008 Apr 2. Crit Care. 2008. PMID: 18384672 Free PMC article.
References
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- Wolkewitz M, Vonberg R-P, Grundmann H, Beyersmann J, Gastmeier P, Baerwolff S, Geffers C, Behnke M, Rueden H, Schumacher M. Risk factors for the development of nosocomial pneumonia and mortality on intensive care units: application of competing risks models. Critical Care. 2008;12:R44. doi: 10.1186/cc6852. - DOI - PMC - PubMed
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- Diggle P, Heagerty P, Liang K-Y, Zeger S. Analysis of Longitudinal Data. 2. New York: Oxford University Press; 2002.
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- Hedeker D, Gibbons RD. Longitudinal Data Analysis. Hoboken, NJ: Wiley; 2006.
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