Design and Analysis of Multiple Events Case–Control Studies
Article first published online: 9 DEC 2009
© 2009, The International Biometric Society
Volume 66, Issue 4, pages 1220–1229, December 2010
How to Cite
Sun, W., Joffe, M. M., Chen, J. and Brunelli, S. M. (2010), Design and Analysis of Multiple Events Case–Control Studies. Biometrics, 66: 1220–1229. doi: 10.1111/j.1541-0420.2009.01369.x
- Issue published online: 9 DEC 2009
- Article first published online: 9 DEC 2009
- Received July 2007. Revised September 2009. Accepted October 2009.
- Case–cohort study;
- Multiple events case–control study;
- Nested case–control study;
- Sampling from a cohort;
- Semiparametric efficient estimator
Summary In case–control research where there are multiple case groups, standard analyses fail to make use of all available information. Multiple events case–control (MECC) studies provide a new approach to sampling from a cohort and are useful when it is desired to study multiple types of events in the cohort. In this design, subjects in the cohort who develop any event of interest are sampled, as well as a fraction of the remaining subjects. We show that a simple case–control analysis of data arising from MECC studies is biased and develop three general estimating-equation-based approaches to analyzing data from these studies. We conduct simulation studies to compare the efficiency of the various MECC analyses with each other and with the corresponding conventional analyses. It is shown that the gain in efficiency by using the new design is substantial in many situations. We demonstrate the application of our approach to a nested case–control study of the effect of oral sodium phosphate use on chronic kidney injury with multiple case definitions.