False Discovery Rate Control under Archimedean Copula

We are considered with the false discovery rate (FDR) of the linear step-up test $\vp^{LSU}$ considered by Benjamini and Hochberg (1995). It is well known that $\vp^{LSU}$ controls the FDR at level $m_0 q / m$ if the joint distribution of $p$-values is multivariate totally positive of order 2. In this, $m$ denotes the total number of hypotheses, $m_0$ the number of true null hypotheses, and $q$ the nominal FDR level. Under the assumption of an Archimedean $p$-value copula with completely monotone generator, we derive a sharper upper bound for the FDR of $\vp^{LSU}$ as well as a non-trivial lower bound. Application of the sharper upper bound to parametric subclasses of Archimedean $p$-value copulae allows us to increase the power of $\vp^{LSU}$ by pre-estimating the copula parameter and adjusting $q$. Based on the lower bound, a sufficient condition is obtained under which the FDR of $\vp^{LSU}$ is exactly equal to $m_0 q / m$, as in the case of stochastically independent $p$-values. Finally, we deal with high-dimensional multiple test problems with exchangeable test statistics by proving that the dependency structure of the corresponding vector of $p$-values can always be expressed by an Archimedean copula with completely monotone generator. Our theoretical results are applied to important copula families, including Clayton copulae and Gumbel copulae.