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A latent class mode...
A latent class model for competing risks
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- Rowley, M. (author)
- Kings Coll London, Inst Math & Mol Biomed, Hodgkin Bldg, London SE1 1UL, England.;Saddle Point Sci, London, England.
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- Garmo, H. (author)
- Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England.
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- Van Hemelrijck, M. (author)
- Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England.
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- Wulaningsih, W. (author)
- Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England.
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- Grundmark, Birgitta (author)
- Uppsala universitet,Endokrinkirurgi,Med Prod Agcy, Uppsala, Sweden
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- Zethelius, Björn (author)
- Uppsala universitet,Geriatrik,Med Prod Agcy, Uppsala, Sweden
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- Hammar, N. (author)
- Karolinska Institutet
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- Walldius, G. (author)
- Karolinska Institutet
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- Inoue, M. (author)
- Waseda Univ, Dept Elect Engn & Biosci, Tokyo, Japan.
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- Holmberg, L. (author)
- Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England.
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- Coolen, A. C. C. (author)
- Kings Coll London, Inst Math & Mol Biomed, Hodgkin Bldg, London SE1 1UL, England.
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Kings Coll London, Inst Math & Mol Biomed, Hodgkin Bldg, London SE1 1UL, England;Saddle Point Sci, London, England. Kings Coll London, Guys Hosp, Canc Epidemiol Grp, London, England. (creator_code:org_t)
- 2017-02-24
- 2017
- English.
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In: Statistics in Medicine. - : Wiley. - 0277-6715 .- 1097-0258. ; 36:13, s. 2100-2119
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Abstract
Subject headings
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- Survival data analysis becomes complex when the proportional hazards assumption is violated at population level or when crude hazard rates are no longer estimators of marginal ones. We develop a Bayesian survival analysis method to deal with these situations, on the basis of assuming that the complexities are induced by latent cohort or disease heterogeneity that is not captured by covariates and that proportional hazards hold at the level of individuals. This leads to a description from which risk-specific marginal hazard rates and survival functions are fully accessible, 'decontaminated' of the effects of informative censoring, and which includes Cox, random effects and latent classmodels as special cases. Simulated data confirm that our approach can map a cohort's substructure and remove heterogeneity-induced informative censoring effects. Application to data from the Uppsala Longitudinal Study of Adult Men cohort leads to plausible alternative explanations for previous counter-intuitive inferences on prostate cancer. The importance of managing cardiovascular disease as a comorbidity in women diagnosed with breast cancer is suggested on application to data from the Swedish Apolipoprotein Mortality Risk Study.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Arbetsmedicin och miljömedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Occupational Health and Environmental Health (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- survival analysis
- heterogeneity
- informative censoring
- competing risks
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Rowley, M.
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Garmo, H.
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Van Hemelrijck, ...
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Wulaningsih, W.
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Grundmark, Birgi ...
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Zethelius, Björn
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show more...
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Hammar, N.
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Walldius, G.
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Inoue, M.
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Holmberg, L.
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Coolen, A. C. C.
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show less...
- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Health Sciences
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and Occupational Hea ...
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Mathematics
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and Probability Theo ...
- Articles in the publication
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Statistics in Me ...
- By the university
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Uppsala University
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Karolinska Institutet