The Romano-Wolf multiple hypothesis correction in stata
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2020
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Abstract
When considering multiple hypothesis tests simultaneously, standard
statistical techniques will lead to over-rejection of null hypotheses unless the
multiplicity of the testing framework is explicitly considered. In this paper
we discuss the Romano-Wolf multiple hypothesis correction, and document its
implementation in Stata. The Romano-Wolf correction (asymptotically) controls
the familywise error rate (FWER), that is, the probability of rejecting at least
one true null hypothesis in a family of hypotheses under test. This correction is
considerably more powerful than earlier multiple testing procedures such as the
Bonferroni and Holm corrections, given that it takes into account the dependence
structure of the test statistics by resampling from the original data. We describe
a Stata command rwolf that implements this correction, and provide a number
of examples based on a wide range of models. We document and discuss the
performance gains from using rwolf over other multiple testing procedures that
control the FWER.
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Stata Journal Volumen: 20 Número: 4 Páginas: 812-843 Dec 2020
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