Estimation of a Concordance Probability for Doubly Censored Time-to-Event Data

Kenichi Hayashi, Yasutaka Shimizu

Research output: Contribution to journalArticle

Abstract

Evaluating the relationship between a response variable and explanatory variables is important to establish better statistical models. Concordance probability is one measure of this relationship and is often used in biomedical research. Concordance probability can be seen as an extension of the area under the receiver operating characteristic curve. In this study, we propose estimators of concordance probability for time-to-event data subject to double censoring. A doubly censored time-to-event response is observed when either left or right censoring may occur. In the presence of double censoring, existing estimators of concordance probability lack desirable properties such as consistency and asymptotic normality. The proposed estimators consist of estimators of the left-censoring and the right-censoring distributions as a weight for each pair of cases, and reduce to the existing estimators in special cases. We show the statistical properties of the proposed estimators and evaluate their performance via numerical experiments.

Original languageEnglish
Pages (from-to)1-22
Number of pages22
JournalStatistics in Biosciences
DOIs
Publication statusAccepted/In press - 2018 Mar 22

Fingerprint

Concordance
Estimator
Left Censoring
Right Censoring
Censoring
Statistical Models
ROC Curve
Biomedical Research
Receiver Operating Characteristic Curve
Asymptotic Normality
Weights and Measures
Statistical property
Statistical Model
Numerical Experiment
Evaluate
Experiments

Keywords

  • Concordance probability
  • Doubly censored data
  • Time-to-event response

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)

Cite this

Estimation of a Concordance Probability for Doubly Censored Time-to-Event Data. / Hayashi, Kenichi; Shimizu, Yasutaka.

In: Statistics in Biosciences, 22.03.2018, p. 1-22.

Research output: Contribution to journalArticle

@article{e202a9cfc3804ddfa0a2e781415abce9,
title = "Estimation of a Concordance Probability for Doubly Censored Time-to-Event Data",
abstract = "Evaluating the relationship between a response variable and explanatory variables is important to establish better statistical models. Concordance probability is one measure of this relationship and is often used in biomedical research. Concordance probability can be seen as an extension of the area under the receiver operating characteristic curve. In this study, we propose estimators of concordance probability for time-to-event data subject to double censoring. A doubly censored time-to-event response is observed when either left or right censoring may occur. In the presence of double censoring, existing estimators of concordance probability lack desirable properties such as consistency and asymptotic normality. The proposed estimators consist of estimators of the left-censoring and the right-censoring distributions as a weight for each pair of cases, and reduce to the existing estimators in special cases. We show the statistical properties of the proposed estimators and evaluate their performance via numerical experiments.",
keywords = "Concordance probability, Doubly censored data, Time-to-event response",
author = "Kenichi Hayashi and Yasutaka Shimizu",
year = "2018",
month = "3",
day = "22",
doi = "10.1007/s12561-018-9216-5",
language = "English",
pages = "1--22",
journal = "Statistics in Biosciences",
issn = "1867-1764",
publisher = "Springer New York",

}

TY - JOUR

T1 - Estimation of a Concordance Probability for Doubly Censored Time-to-Event Data

AU - Hayashi, Kenichi

AU - Shimizu, Yasutaka

PY - 2018/3/22

Y1 - 2018/3/22

N2 - Evaluating the relationship between a response variable and explanatory variables is important to establish better statistical models. Concordance probability is one measure of this relationship and is often used in biomedical research. Concordance probability can be seen as an extension of the area under the receiver operating characteristic curve. In this study, we propose estimators of concordance probability for time-to-event data subject to double censoring. A doubly censored time-to-event response is observed when either left or right censoring may occur. In the presence of double censoring, existing estimators of concordance probability lack desirable properties such as consistency and asymptotic normality. The proposed estimators consist of estimators of the left-censoring and the right-censoring distributions as a weight for each pair of cases, and reduce to the existing estimators in special cases. We show the statistical properties of the proposed estimators and evaluate their performance via numerical experiments.

AB - Evaluating the relationship between a response variable and explanatory variables is important to establish better statistical models. Concordance probability is one measure of this relationship and is often used in biomedical research. Concordance probability can be seen as an extension of the area under the receiver operating characteristic curve. In this study, we propose estimators of concordance probability for time-to-event data subject to double censoring. A doubly censored time-to-event response is observed when either left or right censoring may occur. In the presence of double censoring, existing estimators of concordance probability lack desirable properties such as consistency and asymptotic normality. The proposed estimators consist of estimators of the left-censoring and the right-censoring distributions as a weight for each pair of cases, and reduce to the existing estimators in special cases. We show the statistical properties of the proposed estimators and evaluate their performance via numerical experiments.

KW - Concordance probability

KW - Doubly censored data

KW - Time-to-event response

UR - http://www.scopus.com/inward/record.url?scp=85044272274&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85044272274&partnerID=8YFLogxK

U2 - 10.1007/s12561-018-9216-5

DO - 10.1007/s12561-018-9216-5

M3 - Article

AN - SCOPUS:85044272274

SP - 1

EP - 22

JO - Statistics in Biosciences

JF - Statistics in Biosciences

SN - 1867-1764

ER -