26 research outputs found
Classes of Multiple Decision Functions Strongly Controlling FWER and FDR
This paper provides two general classes of multiple decision functions where
each member of the first class strongly controls the family-wise error rate
(FWER), while each member of the second class strongly controls the false
discovery rate (FDR). These classes offer the possibility that an optimal
multiple decision function with respect to a pre-specified criterion, such as
the missed discovery rate (MDR), could be found within these classes. Such
multiple decision functions can be utilized in multiple testing, specifically,
but not limited to, the analysis of high-dimensional microarray data sets.Comment: 19 page