Survival prediction based on compound covariate under Cox proportional hazard models.
Survival prediction from a large number of covariates is a current focus of statistical and medical research. In this paper, we study a methodology known as the compound covariate prediction performed under univariate Cox proportional hazard models. We demonstrate via simulations and real data analy...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3480451?pdf=render |
| _version_ | 1828173966976483328 |
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| author | Takeshi Emura Yi-Hau Chen Hsuan-Yu Chen |
| author_facet | Takeshi Emura Yi-Hau Chen Hsuan-Yu Chen |
| author_sort | Takeshi Emura |
| collection | DOAJ |
| description | Survival prediction from a large number of covariates is a current focus of statistical and medical research. In this paper, we study a methodology known as the compound covariate prediction performed under univariate Cox proportional hazard models. We demonstrate via simulations and real data analysis that the compound covariate method generally competes well with ridge regression and Lasso methods, both already well-studied methods for predicting survival outcomes with a large number of covariates. Furthermore, we develop a refinement of the compound covariate method by incorporating likelihood information from multivariate Cox models. The new proposal is an adaptive method that borrows information contained in both the univariate and multivariate Cox regression estimators. We show that the new proposal has a theoretical justification from a statistical large sample theory and is naturally interpreted as a shrinkage-type estimator, a popular class of estimators in statistical literature. Two datasets, the primary biliary cirrhosis of the liver data and the non-small-cell lung cancer data, are used for illustration. The proposed method is implemented in R package "compound.Cox" available in CRAN at http://cran.r-project.org/. |
| first_indexed | 2024-04-12T04:04:05Z |
| format | Article |
| id | doaj.art-72d19682e91c4d8594036d5ffb30824b |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-12T04:04:05Z |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-72d19682e91c4d8594036d5ffb30824b2022-12-22T03:48:39ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-01710e4762710.1371/journal.pone.0047627Survival prediction based on compound covariate under Cox proportional hazard models.Takeshi EmuraYi-Hau ChenHsuan-Yu ChenSurvival prediction from a large number of covariates is a current focus of statistical and medical research. In this paper, we study a methodology known as the compound covariate prediction performed under univariate Cox proportional hazard models. We demonstrate via simulations and real data analysis that the compound covariate method generally competes well with ridge regression and Lasso methods, both already well-studied methods for predicting survival outcomes with a large number of covariates. Furthermore, we develop a refinement of the compound covariate method by incorporating likelihood information from multivariate Cox models. The new proposal is an adaptive method that borrows information contained in both the univariate and multivariate Cox regression estimators. We show that the new proposal has a theoretical justification from a statistical large sample theory and is naturally interpreted as a shrinkage-type estimator, a popular class of estimators in statistical literature. Two datasets, the primary biliary cirrhosis of the liver data and the non-small-cell lung cancer data, are used for illustration. The proposed method is implemented in R package "compound.Cox" available in CRAN at http://cran.r-project.org/.http://europepmc.org/articles/PMC3480451?pdf=render |
| spellingShingle | Takeshi Emura Yi-Hau Chen Hsuan-Yu Chen Survival prediction based on compound covariate under Cox proportional hazard models. PLoS ONE |
| title | Survival prediction based on compound covariate under Cox proportional hazard models. |
| title_full | Survival prediction based on compound covariate under Cox proportional hazard models. |
| title_fullStr | Survival prediction based on compound covariate under Cox proportional hazard models. |
| title_full_unstemmed | Survival prediction based on compound covariate under Cox proportional hazard models. |
| title_short | Survival prediction based on compound covariate under Cox proportional hazard models. |
| title_sort | survival prediction based on compound covariate under cox proportional hazard models |
| url | http://europepmc.org/articles/PMC3480451?pdf=render |
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