Multilevel model with random effects for clustered survival data with multiple failure outcomes

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

3 Scopus Citations
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Author(s)

  • Richard Tawiah
  • Kelvin K.W. Yau
  • Geoffrey J. McLachlan
  • Suzanne K. Chambers
  • Shu-Kay Ng

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)1036-1055
Journal / PublicationStatistics in Medicine
Volume38
Issue number6
Online published25 Nov 2018
Publication statusPublished - 15 Mar 2019

Abstract

We present a multilevel frailty model for handling serial dependence and simultaneous heterogeneity in survival data with a multilevel structure attributed to clustering of subjects and the presence of multiple failure outcomes. One commonly observes such data, for example, in multi-institutional, randomized placebo-controlled trials in which patients suffer repeated episodes (eg, recurrent migraines) of the disease outcome being measured. The model extends the proportional hazards model by incorporating a random covariate and unobservable random institution effect to respectively account for treatment-by-institution interaction and institutional variation in the baseline risk. Moreover, a random effect term with correlation structure driven by a first-order autoregressive process is attached to the model to facilitate estimation of between patient heterogeneity and serial dependence. By means of the generalized linear mixed model methodology, the random effects distribution is assumed normal and the residual maximum likelihood and the maximum likelihood methods are extended for estimation of model parameters. Simulation studies are carried out to evaluate the performance of the residual maximum likelihood and the maximum likelihood estimators and to assess the impact of misspecifying random effects distribution on the proposed inference. We demonstrate the practical feasibility of the modeling methodology by analyzing real data from a double-blind randomized multi-institutional clinical trial, designed to examine the effect of rhDNase on the occurrence of respiratory exacerbations among patients with cystic fibrosis.

Research Area(s)

  • GLMM, multilevel frailty model, random baseline risk, random treatment-by-institution interaction, recurrent event data, serial dependence

Citation Format(s)

Multilevel model with random effects for clustered survival data with multiple failure outcomes. / Tawiah, Richard; Yau, Kelvin K.W.; McLachlan, Geoffrey J.; Chambers, Suzanne K.; Ng, Shu-Kay.

In: Statistics in Medicine, Vol. 38, No. 6, 15.03.2019, p. 1036-1055.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review