Attributable Risk Function with Clustered Survival Data
- *Corresponding Author:
- Changchun Xie, PhD
Department of Environmental Health
University of Cincinnati, Ohio, USA
E-mail: [email protected]
Received date: January 04, 2012; Accepted date: March 23, 2012; Published date: March 23, 2012
Citation: Xie C, Lu X, Pogue J (2012) Attributable Risk Function with Clustered Survival Data. J Biomet Biostat S1:007. doi: 10.4172/2155-6180.S1-007
Copyright: © 2012 Xie C, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The Attributable Fraction or risk function (ARF) is used to measure the impact of an exposure on occurrence of disease within a population. For any prospective cohort study, risk is likely to be estimated using time to event or survival data. Attributable risk function with right censored survival data has been discussed by Samuelsen and Eide. We propose a natural extension of the ARF to clustered survival data, which are common in medical research. We derive an estimator of the ARF. Simulation studies are conducted to evaluate the performance of our method and investigate the consequences of ignoring the cluster effect in analysis.