Test for Informative Cluster Size With Right Censored Survival Data

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Test for Informative Cluster Size With Right Censored Survival Data. / Meddis, Alessandra; Latouche, Aurélien.

In: Statistica Sinica, Vol. 34, No. 1, 2024, p. 181-199.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Meddis, A & Latouche, A 2024, 'Test for Informative Cluster Size With Right Censored Survival Data', Statistica Sinica, vol. 34, no. 1, pp. 181-199. https://doi.org/10.5705/ss.202021.0349

APA

Meddis, A., & Latouche, A. (2024). Test for Informative Cluster Size With Right Censored Survival Data. Statistica Sinica, 34(1), 181-199. https://doi.org/10.5705/ss.202021.0349

Vancouver

Meddis A, Latouche A. Test for Informative Cluster Size With Right Censored Survival Data. Statistica Sinica. 2024;34(1):181-199. https://doi.org/10.5705/ss.202021.0349

Author

Meddis, Alessandra ; Latouche, Aurélien. / Test for Informative Cluster Size With Right Censored Survival Data. In: Statistica Sinica. 2024 ; Vol. 34, No. 1. pp. 181-199.

Bibtex

@article{f8c422b90d884f9095da8647de97179c,
title = "Test for Informative Cluster Size With Right Censored Survival Data",
abstract = "Clustered survival data often arise in biomedical research. When the outcome depends on the size of the cluster, the cluster size is said to be informative. Many studies assume a noninformative cluster size, even though it may not always be true. We propose a test for the assumption of informative cluster size in clustered survival data with right censoring. We use standard martingale results to obtain the asymptotic distribution of the test statistic. Simulation studies show that the proposed test works well under various scenarios. To illustrate the proposed approach, we consider several applications: periodontal data, a multicentric study of patients with liver disease, and a recent data set of patients with metastatic cancer treated using immunotherapy.",
keywords = "Clustered data, hypothesis testing, informative cluster size, survival analysis",
author = "Alessandra Meddis and Aur{\'e}lien Latouche",
note = "Publisher Copyright: {\textcopyright} 2024 Institute of Statistical Science. All rights reserved.",
year = "2024",
doi = "10.5705/ss.202021.0349",
language = "English",
volume = "34",
pages = "181--199",
journal = "Statistica Sinica",
issn = "1017-0405",
publisher = "Academia Sinica Institute of Statistical Science",
number = "1",

}

RIS

TY - JOUR

T1 - Test for Informative Cluster Size With Right Censored Survival Data

AU - Meddis, Alessandra

AU - Latouche, Aurélien

N1 - Publisher Copyright: © 2024 Institute of Statistical Science. All rights reserved.

PY - 2024

Y1 - 2024

N2 - Clustered survival data often arise in biomedical research. When the outcome depends on the size of the cluster, the cluster size is said to be informative. Many studies assume a noninformative cluster size, even though it may not always be true. We propose a test for the assumption of informative cluster size in clustered survival data with right censoring. We use standard martingale results to obtain the asymptotic distribution of the test statistic. Simulation studies show that the proposed test works well under various scenarios. To illustrate the proposed approach, we consider several applications: periodontal data, a multicentric study of patients with liver disease, and a recent data set of patients with metastatic cancer treated using immunotherapy.

AB - Clustered survival data often arise in biomedical research. When the outcome depends on the size of the cluster, the cluster size is said to be informative. Many studies assume a noninformative cluster size, even though it may not always be true. We propose a test for the assumption of informative cluster size in clustered survival data with right censoring. We use standard martingale results to obtain the asymptotic distribution of the test statistic. Simulation studies show that the proposed test works well under various scenarios. To illustrate the proposed approach, we consider several applications: periodontal data, a multicentric study of patients with liver disease, and a recent data set of patients with metastatic cancer treated using immunotherapy.

KW - Clustered data

KW - hypothesis testing

KW - informative cluster size

KW - survival analysis

U2 - 10.5705/ss.202021.0349

DO - 10.5705/ss.202021.0349

M3 - Journal article

AN - SCOPUS:85183936667

VL - 34

SP - 181

EP - 199

JO - Statistica Sinica

JF - Statistica Sinica

SN - 1017-0405

IS - 1

ER -

ID: 389670543