1 research outputs found
Bagging multiple comparisons from microarray data
The problem of large-scale simultaneous hypothesis testing is re-visited.
Bagging and subagging procedures are put forth with the purpose of improving
the discovery power of the tests. The procedures are implemented in both
simulated and real data. It is shown that bagging and subagging significantly
improve power at the cost of a small increase in false discovery rate with the
proposed `maximum contrast' subagging having an edge over bagging, i.e.,
yielding similar power but significantly smaller false discovery rates