On Combining Family-Based and Population-Based Case–Control Data in Association Studies
Article first published online: 16 FEB 2010
© 2010, The International Biometric Society No claim to original US government works
Volume 66, Issue 4, pages 1024–1033, December 2010
How to Cite
Zheng, Y., Heagerty, P. J., Hsu, L. and Newcomb, P. A. (2010), On Combining Family-Based and Population-Based Case–Control Data in Association Studies. Biometrics, 66: 1024–1033. doi: 10.1111/j.1541-0420.2010.01393.x
- Issue published online: 16 FEB 2010
- Article first published online: 16 FEB 2010
- Received February 2009. Revised December 2009. Accepted December 2009.
- Conditional likelihood;
- Family studies;
- Outcome-dependent sampling;
- Population-based case–control
Summary Combining data collected from different sources can potentially enhance statistical efficiency in estimating effects of environmental or genetic factors or gene–environment interactions. However, combining data across studies becomes complicated when data are collected under different study designs, such as family-based and unrelated individual-based case–control design. In this article, we describe likelihood-based approaches that permit the joint estimation of covariate effects on disease risk under study designs that include cases, relatives of cases, and unrelated individuals. Our methods accommodate familial residual correlation and a variety of ascertainment schemes. Extensive simulation experiments demonstrate that the proposed methods for estimation and inference perform well in realistic settings. Efficiencies of different designs are contrasted in the simulation. We applied the methods to data from the Colorectal Cancer Family Registry.