Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415365 | Computational Statistics & Data Analysis | 2008 | 11 Pages |
Abstract
In survival analysis, it is of interest to appropriately select significant predictors. In this paper, we extend the AICCAICC selection procedure of Hurvich and Tsai to survival models to improve the traditional AIC for small sample sizes. A theoretical verification under a special case of the exponential distribution is provided. Simulation studies illustrate that the proposed method substantially outperforms its counterpart: AIC, in small samples, and competes it in moderate and large samples. Two real data sets are also analyzed.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Hua Liang, Guohua Zou,