Quantile residual lifetime with right-censored and length-biased data

Peng Liu; Yixin Wang; Yong Zhou

doi:10.1007/s10463-014-0482-9

Quantile residual lifetime with right-censored and length-biased data

Peng Liu
, Yixin Wang
, Yong Zhou^*

^*Corresponding author for this work

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

10 Scopus citations

Abstract

Right-censored length-biased data are commonly encountered in many applications such as cancer screening trials, prevalent cohort studies and labor economics. Such data have a unique structure that is different from traditional survival data. In this paper, we propose an estimator of the quantile residual lifetime (QRL) with this kind of data based on the nonparametric maximum likelihood estimation method. In addition, we develop two tests by taking difference and ratio of the QRL from two independent samples. We also establish the asymptotic properties of the proposed estimator and the test statistics. Simulation studies are performed to demonstrate that the proposed estimator works well in finite-sample situations. We illustrate its application using two data examples: one is the Oscars Award data, the other is the Channing house data.

Original language	English
Pages (from-to)	999-1028
Number of pages	30
Journal	Annals of the Institute of Statistical Mathematics
Volume	67
Issue number	5
DOIs	https://doi.org/10.1007/s10463-014-0482-9
State	Published - 26 Oct 2015
Externally published	Yes

Keywords

Empirical processes
Oscars Award data
Quantile residual lifetime model
Right-censored length-biased data
Two-sample problem

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s10463-014-0482-9

Cite this

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title = "Quantile residual lifetime with right-censored and length-biased data",

abstract = "Right-censored length-biased data are commonly encountered in many applications such as cancer screening trials, prevalent cohort studies and labor economics. Such data have a unique structure that is different from traditional survival data. In this paper, we propose an estimator of the quantile residual lifetime (QRL) with this kind of data based on the nonparametric maximum likelihood estimation method. In addition, we develop two tests by taking difference and ratio of the QRL from two independent samples. We also establish the asymptotic properties of the proposed estimator and the test statistics. Simulation studies are performed to demonstrate that the proposed estimator works well in finite-sample situations. We illustrate its application using two data examples: one is the Oscars Award data, the other is the Channing house data.",

keywords = "Empirical processes, Oscars Award data, Quantile residual lifetime model, Right-censored length-biased data, Two-sample problem",

author = "Peng Liu and Yixin Wang and Yong Zhou",

note = "Publisher Copyright: {\textcopyright} 2014, The Institute of Statistical Mathematics, Tokyo.",

year = "2015",

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doi = "10.1007/s10463-014-0482-9",

language = "英语",

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journal = "Annals of the Institute of Statistical Mathematics",

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}

TY - JOUR

T1 - Quantile residual lifetime with right-censored and length-biased data

AU - Liu, Peng

AU - Wang, Yixin

AU - Zhou, Yong

PY - 2015/10/26

Y1 - 2015/10/26

N2 - Right-censored length-biased data are commonly encountered in many applications such as cancer screening trials, prevalent cohort studies and labor economics. Such data have a unique structure that is different from traditional survival data. In this paper, we propose an estimator of the quantile residual lifetime (QRL) with this kind of data based on the nonparametric maximum likelihood estimation method. In addition, we develop two tests by taking difference and ratio of the QRL from two independent samples. We also establish the asymptotic properties of the proposed estimator and the test statistics. Simulation studies are performed to demonstrate that the proposed estimator works well in finite-sample situations. We illustrate its application using two data examples: one is the Oscars Award data, the other is the Channing house data.

AB - Right-censored length-biased data are commonly encountered in many applications such as cancer screening trials, prevalent cohort studies and labor economics. Such data have a unique structure that is different from traditional survival data. In this paper, we propose an estimator of the quantile residual lifetime (QRL) with this kind of data based on the nonparametric maximum likelihood estimation method. In addition, we develop two tests by taking difference and ratio of the QRL from two independent samples. We also establish the asymptotic properties of the proposed estimator and the test statistics. Simulation studies are performed to demonstrate that the proposed estimator works well in finite-sample situations. We illustrate its application using two data examples: one is the Oscars Award data, the other is the Channing house data.

KW - Empirical processes

KW - Oscars Award data

KW - Quantile residual lifetime model

KW - Right-censored length-biased data

KW - Two-sample problem

UR - https://www.scopus.com/pages/publications/84940033189

U2 - 10.1007/s10463-014-0482-9

DO - 10.1007/s10463-014-0482-9

M3 - 文章

AN - SCOPUS:84940033189

SN - 0020-3157

VL - 67

SP - 999

EP - 1028

JO - Annals of the Institute of Statistical Mathematics

JF - Annals of the Institute of Statistical Mathematics

IS - 5

ER -

Quantile residual lifetime with right-censored and length-biased data

Abstract

Keywords

UN SDGs

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