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Issues in Interpreting Cluster-Based Permutation Tests

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If you have a question about this talk, please contact Johan Carlin.

Cluster-Based Permutation Tests are an attractive tool for statistical analysis of results from neuroimaging experiments. However, despite their upsides, they are routinely employed to justify claims which they – by design – cannot answer; in particular, claims about the temporal or spatial extent of effects. I will discuss what claims are and are not justified by the outcomes of such tests, how to think about them, and provide an outline of how to report these tests in a scientific paper or presentation. I will also briefly discuss some recent developments and alternatives.

While basic knowledge of how Cluster-Based Permutation Tests are employed in cognitive neuroscience will be helpful for following this presentation, I will develop the core issues in a very basic manner, and little understanding of mathematical statistics is expected.

This talk is part of the Imagers Interest Group series.

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