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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25151

Title: Conditional copula models for right-censored clustered event time data.
Authors: Geerdens, Candida
Acar, Elif Fidan
Janssen, Paul
Issue Date: 2017
Citation: BIOSTATISTICS, 19 (2), p. 247-262
Status: Early View
Abstract: We outline an estimation and a testing strategy to infer the impact of a continuous cluster-level covariate on the within-cluster association of right-censored event time data, as modeled through a conditional copula. We propose a local likelihood approach to estimate the copula parameter and we describe a generalized likelihood ratio test to formally assess its constancy. The test decision is based on an approximate p-value obtained via a parametric bootstrap. We evaluate the finite sample performance of the estimation and the testing strategy in a simulation study, under different rates of right-censoring and for various parametric copula families, considering both parametrically and nonparametrically estimated margins. Moreover, the selection of a suitable bandwidth and the impact of a misspecified copula are investigated. Results indicate that the local likelihood approach leads to on target estimation and that the testing strategy has reasonable to high power. Finally, the methods are illustrated on data from the field of medicine.
Notes: Acar, EF (reprint author), Univ Manitoba, Dept Stat, 186 Dysart Rd, Winnipeg, MB R3T 2N2, Canada, elif.acar@umanitoba.ca
URI: http://hdl.handle.net/1942/25151
Link to publication: https://arxiv.org/pdf/1606.01385.pdf
DOI: 10.1093/ biostatistics/kxx034
ISI #: 000429028200009
ISSN: 1465-4644
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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