Department of Biostatistics Seminar/Workshop Series

Estimating Time-varying Effects for Over-dispersed Recurrent Events Data with Cross-over Design

Qingxia (Cindy) Chen, PhD

Assistant Professor, Department of Biostatistics, Vanderbilt University School of Medicine

Wednesday, January 30, 2013, 1:30-2:30pm, MRBIII Room 1220

In the analysis of multivariate event times, frailty models assuming time-independent regression coefficients are often considered, mainly due to their theoretical and numerical convenience. In practice, regression coefficients are often time-dependent and the temporal effects are of clinical interest. Motivated by a phase III clinical trial in multiple sclerosis, we develop a semi-parametric frailty modeling approach to estimate time-varying effects for over-dispersed recurrent events data with Cross-over design. The proposed model naturally incorporates the treatment switching time in the time-varying coefficients. Simulation studies evaluate the numerical performance of the proposed model under various temporal treatment effect curves. The ideas in this paper can also be used for time-varying coefficient frailty models without treatment switching as well as for alternative models when the proportional hazard assumption is violated. A multiple sclerosis dataset is analyzed to illustrate our methodology.