The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Applying Cox Regression to Competing Risks
Abstract
Two methods are given for the joint estimation of parameters in models for competing risks in survival analysis. In both cases Cox's proportional hazards regression model is fitted using a data duplication method. In principle either method can be used for any number of different failure types, assuming independent risks. Advantages of the augmented data approach are that it limits over-parametrisation and it runs immediately on existing software. The methods are used to reanalyse data from two well-known published studies, providing new insights.
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Citations
Cites
Regression analysis of multivariate incomplete failure time data by modeling marginal distributions
Wei, L. J., Lin, D. Y., & Weissfeld, L. (1989) · Journal of the American Statistical Association · doi:10.1080/01621459.1989.10478873 · Cited by 1,868
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Low-Dose Methotrexate for the Prevention of Atherosclerotic Events
Ridker, P. M., Everett, B. M., Pradhan, A., MacFadyen, J. G., Solomon, D. H., Zaharris, E., Mam, V., Hasan, A., Rosenberg, Y., Iturriaga, E., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1809798 · Cited by 1,317
Khan, S. S., Ning, H., Wilkins, J. T., Allen, N., Carnethon, M., Berry, J. D., Sweis, R. N., & Lloyd-Jones, D. M. (2018) · JAMA Cardiology · doi:10.1001/jamacardio.2018.0022 · Cited by 1,072
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Metadata
- Authors
- Lunn, M., & McNeil, D.
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1995-06
- Volume
- 51
- Issue
- 2
- Pages
- 524
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2073023604
- Cited by
- 975
- References
- 1
- FWCI
- 1.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lunn, M., & McNeil, D. (1995). Applying Cox Regression to Competing Risks. Biometrics. https://doi.org/10.2307/2532940
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
