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Abstract:
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Of late much attention has been focused on problems of reproducibility in the scientific literature, with many published studies failing to meet what seems a minimal standard. Functional neuroimaging research has not been immune to these criticisms. As a reaction to the "reproduciblity crisis" in science, a variety of solutions have been proposed, most of which touch on, in one way or another, issues of multiple testing and Type I error control. In this talk, I will discuss the question of reproducibility in functional neuroimaging and other large-scale data settings, via the perspective of multiplicity.
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