Variable selection in the accelerated failure time model via the bridge method.

ABSTRACT: In high throughput genomic studies, an important goal is to identify a small number of genomic markers that are associated with development and progression of diseases. A representative example is microarray prognostic studies, where the goal is to identify genes whose expressions are associated with disease free or overall survival. Because of the high dimensionality of gene expression data, standard survival analysis techniques cannot be directly applied. In addition, among the thousands of genes surveyed, only a subset are disease-associated. Gene selection is needed along with estimation. In this article, we model the relationship between gene expressions and survival using the accelerated failure time (AFT) models. We use the bridge penalization for regularized estimation and gene sel

SUBMITTER: Huang J 

PROVIDER: S-EPMC2989175 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature