Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1997-4-29
pubmed:abstractText
I propose a new method for variable selection and shrinkage in Cox's proportional hazards model. My proposal minimizes the log partial likelihood subject to the sum of the absolute values of the parameters being bounded by a constant. Because of the nature of this constraint, it shrinks coefficients and produces some coefficients that are exactly zero. As a result it reduces the estimation variance while providing an interpretable final model. The method is a variation of the 'lasso' proposal of Tibshirani, designed for the linear regression context. Simulations indicate that the lasso can be more accurate than stepwise selection in this setting.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
28
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
385-95
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1997
pubmed:articleTitle
The lasso method for variable selection in the Cox model.
pubmed:affiliation
Department of Preventive Medicine and Biostatistics, University of Toronto, Ontario, Canada.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't