Analysis of Heart Transplant Survival Data Using Generalized Additive Models

The Stanford Heart Transplant data were collected to model survival in patients using penalized smoothing splines for covariates whose values change over the course of the study. The basic idea of the present study is to use a logistic regression model and a generalized additive model with B-splines...

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Detalles Bibliográficos
Autores principales: Tsujitani, Masaaki, Tanaka, Yusuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3676996/
https://www.ncbi.nlm.nih.gov/pubmed/23762190
http://dx.doi.org/10.1155/2013/609857
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author Tsujitani, Masaaki
Tanaka, Yusuke
author_facet Tsujitani, Masaaki
Tanaka, Yusuke
author_sort Tsujitani, Masaaki
collection PubMed
description The Stanford Heart Transplant data were collected to model survival in patients using penalized smoothing splines for covariates whose values change over the course of the study. The basic idea of the present study is to use a logistic regression model and a generalized additive model with B-splines to estimate the survival function. We model survival time as a function of patient covariates and transplant status and compare the results obtained using smoothing spline, partial logistic, Cox's proportional hazards, and piecewise exponential models.
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spelling pubmed-36769962013-06-12 Analysis of Heart Transplant Survival Data Using Generalized Additive Models Tsujitani, Masaaki Tanaka, Yusuke Comput Math Methods Med Research Article The Stanford Heart Transplant data were collected to model survival in patients using penalized smoothing splines for covariates whose values change over the course of the study. The basic idea of the present study is to use a logistic regression model and a generalized additive model with B-splines to estimate the survival function. We model survival time as a function of patient covariates and transplant status and compare the results obtained using smoothing spline, partial logistic, Cox's proportional hazards, and piecewise exponential models. Hindawi Publishing Corporation 2013 2013-05-23 /pmc/articles/PMC3676996/ /pubmed/23762190 http://dx.doi.org/10.1155/2013/609857 Text en Copyright © 2013 M. Tsujitani and Y. Tanaka. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Tsujitani, Masaaki
Tanaka, Yusuke
Analysis of Heart Transplant Survival Data Using Generalized Additive Models
title Analysis of Heart Transplant Survival Data Using Generalized Additive Models
title_full Analysis of Heart Transplant Survival Data Using Generalized Additive Models
title_fullStr Analysis of Heart Transplant Survival Data Using Generalized Additive Models
title_full_unstemmed Analysis of Heart Transplant Survival Data Using Generalized Additive Models
title_short Analysis of Heart Transplant Survival Data Using Generalized Additive Models
title_sort analysis of heart transplant survival data using generalized additive models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3676996/
https://www.ncbi.nlm.nih.gov/pubmed/23762190
http://dx.doi.org/10.1155/2013/609857
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