Journal article

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

Richard Tawiah, Kelvin KW Yau, Geoffrey J McLachlan, Suzanne K Chambers, Shu-Kay Ng

Statistics in Medicine | John Wiley and Sons | Published : 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 r..

View full abstract

University of Melbourne Researchers