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Survival Data Analysis with Time-Dependent Covariates Using Generalized Additive Models
Joint Authors
Sakon, Masato
Tanaka, Yusuke
Tsujitani, Masaaki
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-04-01
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
We discuss a flexible method for modeling survival data using penalized smoothing splines when the values of covariates change for the duration of the study.
The Cox proportional hazards model has been widely used for the analysis of treatment and prognostic effects with censored survival data.
However, a number of theoretical problems with respect to the baseline survival function remain unsolved.
We use the generalized additive models (GAMs) with B splines to estimate the survival function and select the optimum smoothing parameters based on a variant multifold cross-validation (CV) method.
The methods are compared with the generalized cross-validation (GCV) method using data from a long-term study of patients with primary biliary cirrhosis (PBC).
American Psychological Association (APA)
Tsujitani, Masaaki& Tanaka, Yusuke& Sakon, Masato. 2012. Survival Data Analysis with Time-Dependent Covariates Using Generalized Additive Models. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-513780
Modern Language Association (MLA)
Tsujitani, Masaaki…[et al.]. Survival Data Analysis with Time-Dependent Covariates Using Generalized Additive Models. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-9.
https://search.emarefa.net/detail/BIM-513780
American Medical Association (AMA)
Tsujitani, Masaaki& Tanaka, Yusuke& Sakon, Masato. Survival Data Analysis with Time-Dependent Covariates Using Generalized Additive Models. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-9.
https://search.emarefa.net/detail/BIM-513780
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-513780