Mixture cure models with time-varying and multilevel frailties for recurrent event data
Richard Tawiah, Geoffrey McLachlan, Shu Kay Ng
Statistical Methods in Medical Research | SAGE Publications | Published : 2019
Many medical studies yield data on recurrent clinical events from populations which consist of a proportion of cured patients in the presence of those who experience the event at several times (uncured). A frailty mixture cure model has recently been postulated for such data, with an assumption that the random subject effect (frailty) of each uncured patient is constant across successive gap times between recurrent events. We propose two new models in a more general setting, assuming a multivariate time-varying frailty with an AR(1) correlation structure for each uncured patient and addressing multilevel recurrent event data originated from multi-institutional (multi-centre) clinical trials,..View full abstract
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: RT gratefully acknowledges the financial support from Griffith University International Postgraduate Research Scholarship and Griffith University Postgraduate Research Scholarship (HTH). SKN and GJM acknowledge the support of a Discovery Grant from the Australian Research Council.