A combined gamma frailty and normal random-effects model for repeated, overdispersed time-to-event data

This paper presents, extends, and studies a model for repeated, overdispersed time-to-event outcomes, subject to censoring. Building upon work by Molenberghs, Verbeke en Demétrio(2007) and Molenberghs et al. (2010), gamma and normal random effects are included in a Weibull model, to account for overdispersion and between-subjects effects, respectively. Unlike these authors, censoring is allowed for. Two estimation methods are presented. The partial marginalization approach to full maximum likelihood of Molenberghs et al. (2010) is contrasted with pseudo-likelihood estimation. A limited simulation study is conducted to examine the relative merits of these estimation methods. The modeling framework is employed to analyze data on recurrent asthma attacks in children on the one hand and on survival in cancer patients on the other.

Publication year:2014

Keywords:exponential model, generalized Cauchy distribution, conjugacy, maximum likelihood, frailty model, pseudo-likelihood, strong conjugacy, Weibull model

BOF-keylabel:yes

IOF-keylabel:yes

BOF-publication weight:6

CSS-citation score:1

Authors:International

Authors from:Higher Education

Accessibility:Open