Article first published online: 17 SEP 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 32, Issue 9, pages 1494–1508, 30 April 2013
How to Cite
Chen, H. Y., Kittles, R. and Zhang, W. (2013), Bias correction to secondary trait analysis with case–control design. Statist. Med., 32: 1494–1508. doi: 10.1002/sim.5613
- Issue published online: 10 APR 2013
- Article first published online: 17 SEP 2012
- Manuscript Accepted: 21 AUG 2012
- Manuscript Received: 13 SEP 2011
- NSF. Grant Number: DMS 1007726
- extreme-value sampling design;
- semi-parametric likelihood;
- odds ratio model;
- sensitivity analysis
In genetic association studies with densely typed genetic markers, it is often of substantial interest to examine not only the primary phenotype but also the secondary traits for their association with the genetic markers. For more efficient sample ascertainment of the primary phenotype, a case–control design or its variants, such as the extreme-value sampling design for a quantitative trait, are often adopted. The secondary trait analysis without correcting for the sample ascertainment may yield a biased association estimator. We propose a new method aiming at correcting the potential bias due to the inadequate adjustment of the sample ascertainment. The method yields explicit correction formulas that can be used to both screen the genetic markers and rapidly evaluate the sensitivity of the results to the assumed baseline case-prevalence rate in the population. Simulation studies demonstrate good performance of the proposed approach in comparison with the more computationally intensive approaches, such as the compensator approaches and the maximum prospective likelihood approach. We illustrate the application of the approach by analysis of the genetic association of prostate specific antigen in a case–control study of prostate cancer in the African American population. Copyright © 2012 John Wiley & Sons, Ltd.