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Are you sure about that? As I understand it, they are testing a really-really-null hypothesis. Specifically, they started with some resting state data (a condi

Are you sure about that? As I understand it, they are testing a really-really-null hypothesis. Specifically, they started with some resting state data (a condition where the subjects just lie there, attempting to remain alive). They then took this data and imposed fake task structures over it, as if the subject were doing two different things (e.g., condition #1 starts at t=0, t=1 min, t=3 min, t=6 min; condition #2 starts at t=2, t=4, t=5 min). Once this is done, the task+data is submitted to their analysis pipeline. The null hypothesis (fake condition #1 == fake condition #2) has to be true, by construction. This assumes that the original data doesn't have any structure, which may or may not be true (they discuss it a bit towards the end of the paper).

nonbel 10y ago
>"The null hypothesis (fake condition #1 == fake condition #2) has to be true, by construction." The null hypothesis is not only that condition 1 == condition 2, it involves other assumptions being made. From their own description, they knew it was false before even doing this analysis and used this knowledge to design the study. Apparently there is some incorrect assumption about autocorrelation being made. It seems the authors did not really grasp what hypothesis they were testing, leading to their confused (but still productive) description of the problem. I go into more in this post: https://news.ycombinator.com/item?id=12032772 https://news.ycombinator.com/item?id=12032772