Objectives Procedures for controlling the false positive rate when performing many
hypothesis tests are commonplace in health and medical studies. Such procedures, most …

In the last decade a growing amount of statistical research has been devoted to multiple
testing, motivated by a variety of applications in medicine, bioinformatics, genomics, brain …

Hundreds of papers and factors attempt to explain the cross-section of expected returns.
Given this extensive data mining, it does not make sense to use the usual criteria for …

In the post-genomic era, the elucidation of the relationship between the molecular origins of
diseases and their resulting phenotypes is a crucial task for medical research. Here, we use …

A basic task in the analysis of count data from RNA-seq is the detection of differentially
expressed genes. The count data are presented as a table which reports, for each sample …

Importance Recent genome-wide association studies (GWAS) and pathway analyses
supported long-standing observations of an association between immune-mediated …

The problem of multiple comparisons is discussed in the context of medical research. The
need for more powerful procedures than classical multiple comparison procedures is …

The linear step-up multiple testing procedure controls the false discovery rate at the desired
level q for independent and positively dependent test statistics. When all null hypotheses are …

Multiple testing refers to the testing of more than one hypothesis at a time. It is a subfield of
the broader field of multiple inference, or simultaneous inference, which includes multiple …

A basic task in the analysis of count data from RNA-Seq is the detection of differentially
expressed genes. The count data are presented as a table which reports, for each sample …