Multigroup Equivalence Analysis for High-Dimensional Expression Data.

ABSTRACT: Hypothesis tests of equivalence are typically known for their application in bioequivalence studies and acceptance sampling. Their application to gene expression data, in particular high-dimensional gene expression data, has only recently been studied. In this paper, we examine how two multigroup equivalence tests, the F-test and the range test, perform when applied to microarray expression data. We adapted these tests to a well-known equivalence criterion, the difference ratio. Our simulation results showed that both tests can achieve moderate power while controlling the type I error at nominal level for typical expression microarray studies with the benefit of easy-to-interpret equivalence limits. For the range of parameters simulated in this paper, the F-test is more powerful than the r

SUBMITTER: Yang C 

PROVIDER: S-EPMC4659441 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature