Modelling hierarchical clustered censored data with the hierarchical Kendall copula

Chien Lin Su, Johanna G. Nešlehová*, Weijing Wang

*Korrespondierende*r Autor*in für diese Arbeit

Publikation: Wissenschaftliche FachzeitschriftOriginalbeitrag in FachzeitschriftBegutachtung

Abstract

This article proposes a new model for right-censored survival data with multi-level clustering based on the hierarchical Kendall copula model of Brechmann (2014) with Archimedean clusters. This model accommodates clusters of unequal size and multiple clustering levels, without imposing any structural conditions on the parameters or on the copulas used at various levels of the hierarchy. A step-wise estimation procedure is proposed and shown to yield consistent and asymptotically Gaussian estimates under mild regularity conditions. The model fitting is based on multiple imputation, given that the censoring rate increases with the level of the hierarchy. To check the model assumption of Archimedean dependence, a goodness-of test is developed. The finite-sample performance of the proposed estimators and of the goodness-of-fit test is investigated through simulations. The new model is applied to data from the study of chronic granulomatous disease.

OriginalspracheEnglisch
Seiten (von - bis)182-203
Seitenumfang22
FachzeitschriftCanadian Journal of Statistics
Jahrgang47
Ausgabenummer2
DOIs
PublikationsstatusVeröffentlicht - Juni 2019
Extern publiziertJa

Bibliographische Notiz

Funding Information:
The authors thank the Editor, the Associate Editor and an anonymous referee whose comments led to a substantial improvement in the article. Chien-Lin Su and Weijing Wang gratefully acknowledge the financial support of the Taiwanese Ministry of Science and Technology. Partial funding in support of Johanna G. Nešlehová’s research was provided by the Natural Sciences and Engineering Research Council of Canada, the Canadian Statistical Sciences Institute, and the Fonds de Recherche du Québec – Nature et Technologies.

Publisher Copyright:
© 2019 Statistical Society of Canada / Société statistique du Canada

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