No. 991

Title:

A conservative test for multiple comparison based on highly correlated test statistics

Author(s):

Ninomiya, Yoshiyuki (Graduate School of Mathematics, Kyushu University);
Fujisawa, Hironori (The Institute of Statistical Mathematics)

Key words:

Bonferroni's bound, Epidemic change detection, QTL detection, Signal detection, Two-point bound, W bound.

Abstract:

    In genetics and epidemiology, we often encounter a large number of highly correlated test statistics. The most famous conservative bound for multiple comparison is the Bonferroni's bound, which is suitable when the test statistics are independent but not when the test statistics are highly correlated. This paper proposes a new conservative bound, which 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 study and real data analysis.