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The Survival Kit: Software to analyze survival data including possibly correlated random effects

The Survival Kit is a Fortran 90 Software intended for survival analysis using proportional hazards models and their extension to frailty models with a single response time. The hazard function is described as the product of a baseline hazard function and a positive (exponential) function of possibl...

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Detalles Bibliográficos
Autores principales: Mészáros, G., Sölkner, J., Ducrocq, V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Scientific Publishers 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3693034/
https://www.ncbi.nlm.nih.gov/pubmed/23399103
http://dx.doi.org/10.1016/j.cmpb.2013.01.010
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author Mészáros, G.
Sölkner, J.
Ducrocq, V.
author_facet Mészáros, G.
Sölkner, J.
Ducrocq, V.
author_sort Mészáros, G.
collection PubMed
description The Survival Kit is a Fortran 90 Software intended for survival analysis using proportional hazards models and their extension to frailty models with a single response time. The hazard function is described as the product of a baseline hazard function and a positive (exponential) function of possibly time-dependent fixed and random covariates. Stratified Cox, grouped data and Weibull models can be used. Random effects can be either log-gamma or normally distributed and can account for a pedigree structure. Variance parameters are estimated in a Bayesian context. It is possible to account for the correlated nature of two random effects either by specifying a known correlation coefficient or estimating it from the data. An R interface of the Survival Kit provides a user friendly way to run the software.
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spelling pubmed-36930342013-06-26 The Survival Kit: Software to analyze survival data including possibly correlated random effects Mészáros, G. Sölkner, J. Ducrocq, V. Comput Methods Programs Biomed Article The Survival Kit is a Fortran 90 Software intended for survival analysis using proportional hazards models and their extension to frailty models with a single response time. The hazard function is described as the product of a baseline hazard function and a positive (exponential) function of possibly time-dependent fixed and random covariates. Stratified Cox, grouped data and Weibull models can be used. Random effects can be either log-gamma or normally distributed and can account for a pedigree structure. Variance parameters are estimated in a Bayesian context. It is possible to account for the correlated nature of two random effects either by specifying a known correlation coefficient or estimating it from the data. An R interface of the Survival Kit provides a user friendly way to run the software. Elsevier Scientific Publishers 2013-06 /pmc/articles/PMC3693034/ /pubmed/23399103 http://dx.doi.org/10.1016/j.cmpb.2013.01.010 Text en © 2013 Elsevier Ireland Ltd. https://creativecommons.org/licenses/by-nc-nd/3.0/ Open Access under CC BY-NC-ND 3.0 (https://creativecommons.org/licenses/by-nc-nd/3.0/) license
spellingShingle Article
Mészáros, G.
Sölkner, J.
Ducrocq, V.
The Survival Kit: Software to analyze survival data including possibly correlated random effects
title The Survival Kit: Software to analyze survival data including possibly correlated random effects
title_full The Survival Kit: Software to analyze survival data including possibly correlated random effects
title_fullStr The Survival Kit: Software to analyze survival data including possibly correlated random effects
title_full_unstemmed The Survival Kit: Software to analyze survival data including possibly correlated random effects
title_short The Survival Kit: Software to analyze survival data including possibly correlated random effects
title_sort survival kit: software to analyze survival data including possibly correlated random effects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3693034/
https://www.ncbi.nlm.nih.gov/pubmed/23399103
http://dx.doi.org/10.1016/j.cmpb.2013.01.010
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