Name
Abstract | ||
|---|---|---|
The requirement of constant censoring parameter @b in Koziol-Green (KG) model is too restrictive. When covariates are present, the conditional KG model (Veraverbekea and Cadarso-Suarez, 2000) which allows @b to be dependent on the covariates is more realistic. In this paper, using sufficient dimension reduction methods, we provide a model-free diagnostic tool to test if @b is a function of the covariates. Our method also allows us to conduct a model-free selection of the related covariates. A simulation study and a real data analysis are also included to illustrate our approach. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.csda.2010.02.022 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
constant censoring parameter,multiple covariates,conditional kg model,conditional koziol–green model,sufficient dimension reduction,sufficient dimension reduction method,proportional censorship model,related covariates,simulation study,model-free diagnostic tool,real data analysis,proportional hazards model,model-free selection,data analysis,proportional hazard model,dimension reduction | Econometrics,Covariate,Proportional hazards model,Statistics,Sufficient dimension reduction,Censoring (statistics),Mathematics | Journal |
Volume | Issue | ISSN |
54 | 8 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuerong Meggie Wen | 1 | 2 | 1.23 |