I would do another rapid peer-review by twitter here, but honestly it's such a garbage fire of a paper that I can't see the point?https://twitter.com/MicrobiomDigest/status/1270146784652693505 …
Epidemiologist. Writer (Guardian, Observer etc). "Well known research trouble-maker". PhDing at @UoW Host of @senscipod Email gidmk.healthnerd@gmail.com he/him
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Health Nerd Retweeted Elisabeth Bik
I would do another rapid peer-review by twitter here, but honestly it's such a garbage fire of a paper that I can't see the point?https://twitter.com/MicrobiomDigest/status/1270146784652693505 …
Health Nerd added,
Their risk of bias rating was basically "does this study agree with me?". They transformed numbers weirdly to give odds ratios that they then inappropriately plugged into a single statistical model
There was no meaningful distinction between Big Data and/or real world, and the disconnect made no sense. The papers they liked appear multiple times in the analysis, but the ones they disliked only get a single line (for no reason)
Agreed. They appear to have basically decided that research that they didn't like was "Big Data" and then derided it as Very Bad
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