Name
Title | ||
|---|---|---|
Robust Smoothed Rank Estimation Methods for Accelerated Failure Time Model Allowing Clusters. |
Abstract | ||
|---|---|---|
Smoothed Gehan rank estimation methods are widely used in accelerated failure time (AFT) models with/without clusters. However, most methods are sensitive to outliers in the covariates. In order to solve this problem, we propose robust approaches based on the smoothed Gehan rank estimation methods for the AFT model, allowing for clusters by employing two different weight functions. Simulation studies show that the proposed methods outperform existing smoothed rank estimation methods regarding their biases and standard deviations when there are outliers in the covariates. The proposed methods are also applied to a real dataset from the Major cardiovascular interventions study. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1080/03610918.2014.882944 | COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION |
Keywords | DocType | Volume |
Accelerated failure time model,Clusters,Gehan rank estimation,Robust,62N01,62N02,62H12 | Journal | 45 |
Issue | ISSN | Citations |
6 | 0361-0918 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ji Luo | 1 | 0 | 0.34 |
| Haifen Li | 2 | 0 | 0.34 |
| Jiajia Zhang | 3 | 26 | 16.64 |