Model-free predictor tests in survival regression through sufficient dimension reduction

Jae Keun Yoo; Keunbaik Lee

doi:10.1007/s10985-010-9187-4

Model-free predictor tests in survival regression through sufficient dimension reduction

Jae Keun Yoo, Keunbaik Lee

Department of Statistics

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

In this article, we test the effects of predictors in survival regression through two well-known sufficient dimension reduction methods. Since the usual sufficient dimension reduction methods do not require pre-specified models, the predictor effect tests can be considered model-free. All of the test statistics have χ² distributions. Numerical studies of the proposed predictor effect tests in various simulations and real data application are presented.

Original language	English
Pages (from-to)	433-444
Number of pages	12
Journal	Lifetime Data Analysis
Volume	17
Issue number	3
DOIs	https://doi.org/10.1007/s10985-010-9187-4
State	Published - Jul 2011

Bibliographical note

Funding Information:
Acknowledgements The authors are also grateful to the referees for many helpful comments. For Jae Keun Yoo, this work was supported by Basic Science Research Program through the National Research Foundation of Korea (KRF) funded by the Ministry of Education, Science and Technology (2010-0003189). The authors would like to thank Joseph Hagan from the Biostatistics program at Louisiana State University Health Sciences Center for his suggestions and inputs.

Keywords

Inverse regression
Ordinary least square
Predictor tests
Sufficient dimension reduction
Survival regression

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10.1007/s10985-010-9187-4

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abstract = "In this article, we test the effects of predictors in survival regression through two well-known sufficient dimension reduction methods. Since the usual sufficient dimension reduction methods do not require pre-specified models, the predictor effect tests can be considered model-free. All of the test statistics have χ2 distributions. Numerical studies of the proposed predictor effect tests in various simulations and real data application are presented.",

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Model-free predictor tests in survival regression through sufficient dimension reduction

Abstract

Bibliographical note

Keywords

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