Profile likelihood approaches for semiparametric copula and frailty models for clustered survival data

Il Do Ha*, Jong Min Kim, Takeshi Emura

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

9 Scopus citations

Abstract

In clustered survival data, the dependence among individual survival times within a cluster has usually been described using copula models and frailty models. In this paper we propose a profile likelihood approach for semiparametric copula models with different cluster sizes. We also propose a likelihood ratio method based on profile likelihood for testing the absence of association parameter (i.e. test of independence) under the copula models, leading to the boundary problem of the parameter space. For this purpose, we show via simulation study that the proposed likelihood ratio method using an asymptotic chi-square mixture distribution performs well as sample size increases. We compare the behaviors of the two models using the profile likelihood approach under a semiparametric setting. The proposed method is demonstrated using two well-known data sets.

Original languageEnglish
Pages (from-to)2553-2571
Number of pages19
JournalJournal of Applied Statistics
Volume46
Issue number14
DOIs
StatePublished - 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Copula models
  • marginal likelihood
  • profile likelihood
  • random effect
  • semi-parametric frailty models

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