Abstract
In genetics, we often encounter a large number of highly correlated test statistics. The most famous conservative bound for multiple comparison is Bonferroni's bound, which is suitable when the test statistics are independent but not when the test statistics are highly correlated. This article proposes a new conservative bound that is easily calculated without multiple integration and is a good approximation when the test statistics are highly correlated. The performance of the proposed method is evaluated by simulation and real data analysis.
| Original language | English |
|---|---|
| Pages (from-to) | 1135-1142 |
| Number of pages | 8 |
| Journal | Biometrics |
| Volume | 63 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec 2007 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
- Applied Mathematics