Analysis of Nested CGD Infection Data Using Multilevel Frailty Model

Multivariate event-time data with nested structures can be modelled by random-effect survival models such as multilevel frailty models. We show how to analyze the chronic granulomatous disease data(Fleming and Harrington, 1991), which comprise recurrent infection times of patients from different hospitals, using multilevel frailty model. Inferences are developed using hierarchical-likelihood, which provides a simple unified framework and a numerically efficient fitting algorithm for various random-effect models.