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arxiv: 1810.02669 · v1 · pith:OLYQDQFXnew · submitted 2018-10-05 · 📊 stat.AP

Reply to Chen et al.: Parametric methods for cluster inference perform worse for two-sided t-tests

classification 📊 stat.AP
keywords two-sidedone-sidedtestsmethodsperformt-testsclusterparametric
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One-sided t-tests are commonly used in the neuroimaging field, but two-sided tests should be the default unless a researcher has a strong reason for using a one-sided test. Here we extend our previous work on cluster false positive rates, which used one-sided tests, to two-sided tests. Briefly, we found that parametric methods perform worse for two-sided t-tests, and that non-parametric methods perform equally well for one-sided and two-sided tests.

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