A homoscedasticity test for the accelerated failure time model

Lili Yu; Liang Liu; Ding Geng Chen

doi:10.1007/s00180-018-0840-9

A homoscedasticity test for the accelerated failure time model

Lili Yu, Liang Liu, Ding Geng Chen

Biostatistics, Epidemiology, & Environmental Health Sciences

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

2 Scopus citations

Abstract

The semiparametric accelerated failure time (AFT) model is a popular linear model in survival analysis. AFT model and its associated inference methods assume homoscedasticity of the survival data. It is shown that violation of this assumption will lead to inefficient parameter estimation and anti-conservative confidence interval estimation, and thus, misleading conclusions in survival data analysis. However, there is no valid statistical test proposed to test the homoscedasticity assumption. In this paper, we propose the first novel quasi-likelihood ratio test for the homoscedasticity assumption in the AFT model. Simulation studies show the test performs well. A real dataset is used to demonstrate the usefulness of the developed test.

Original language	English
Pages (from-to)	433-446
Number of pages	14
Journal	Computational Statistics
Volume	34
Issue number	1
DOIs	https://doi.org/10.1007/s00180-018-0840-9
State	Published - Mar 5 2019

Keywords

Accelerated failure time model
Homoscedasticity test
Quasi-likelihood ratio test
Right censoring
Survival analysis

Access to Document

10.1007/s00180-018-0840-9

Cite this

@article{9377aea6d1b04b12b5f1cf8ae5ac9b59,

title = "A homoscedasticity test for the accelerated failure time model",

abstract = "The semiparametric accelerated failure time (AFT) model is a popular linear model in survival analysis. AFT model and its associated inference methods assume homoscedasticity of the survival data. It is shown that violation of this assumption will lead to inefficient parameter estimation and anti-conservative confidence interval estimation, and thus, misleading conclusions in survival data analysis. However, there is no valid statistical test proposed to test the homoscedasticity assumption. In this paper, we propose the first novel quasi-likelihood ratio test for the homoscedasticity assumption in the AFT model. Simulation studies show the test performs well. A real dataset is used to demonstrate the usefulness of the developed test.",

keywords = "Accelerated failure time model, Homoscedasticity test, Quasi-likelihood ratio test, Right censoring, Survival analysis",

author = "Lili Yu and Liang Liu and Chen, {Ding Geng}",

note = "Publisher Copyright: {\textcopyright} 2018, Springer-Verlag GmbH Germany, part of Springer Nature.",

year = "2019",

month = mar,

day = "5",

doi = "10.1007/s00180-018-0840-9",

language = "English",

volume = "34",

pages = "433--446",

journal = "Computational Statistics",

issn = "0943-4062",

publisher = "Springer Verlag",

number = "1",

}

TY - JOUR

T1 - A homoscedasticity test for the accelerated failure time model

AU - Yu, Lili

AU - Liu, Liang

AU - Chen, Ding Geng

PY - 2019/3/5

Y1 - 2019/3/5

N2 - The semiparametric accelerated failure time (AFT) model is a popular linear model in survival analysis. AFT model and its associated inference methods assume homoscedasticity of the survival data. It is shown that violation of this assumption will lead to inefficient parameter estimation and anti-conservative confidence interval estimation, and thus, misleading conclusions in survival data analysis. However, there is no valid statistical test proposed to test the homoscedasticity assumption. In this paper, we propose the first novel quasi-likelihood ratio test for the homoscedasticity assumption in the AFT model. Simulation studies show the test performs well. A real dataset is used to demonstrate the usefulness of the developed test.

AB - The semiparametric accelerated failure time (AFT) model is a popular linear model in survival analysis. AFT model and its associated inference methods assume homoscedasticity of the survival data. It is shown that violation of this assumption will lead to inefficient parameter estimation and anti-conservative confidence interval estimation, and thus, misleading conclusions in survival data analysis. However, there is no valid statistical test proposed to test the homoscedasticity assumption. In this paper, we propose the first novel quasi-likelihood ratio test for the homoscedasticity assumption in the AFT model. Simulation studies show the test performs well. A real dataset is used to demonstrate the usefulness of the developed test.

KW - Accelerated failure time model

KW - Homoscedasticity test

KW - Quasi-likelihood ratio test

KW - Right censoring

KW - Survival analysis

UR - http://www.scopus.com/inward/record.url?scp=85053924268&partnerID=8YFLogxK

U2 - 10.1007/s00180-018-0840-9

DO - 10.1007/s00180-018-0840-9

M3 - Article

SN - 0943-4062

VL - 34

SP - 433

EP - 446

JO - Computational Statistics

JF - Computational Statistics

IS - 1

ER -

A homoscedasticity test for the accelerated failure time model

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this