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by @danabra.mov
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by @danabra.mov
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by @jimpick.com
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by @atsui.org
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This is an interesting paper on power in computational modelling, with several useful points. But I think the headline conclusion — that 60–80% of studies are underpowered — rests on a very specific effect-size assumption that is hard to justify and unlikely to be realistic in most cases. 1/5
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Matteo Lisi
Happy to share my new paper published in @nathumbehav.nature.com: A critical look at statistical power in computational modeling studies, particularly those based on model selection. www.nature.com/articles/s41...