Lol that's actually hilarious There are certainly possible criticisms, but since they used rigorous measures of diabetes/smoking/obesity and controlled for these in their analysis, this is not one of them Pure tribalism!pic.twitter.com/kuzsa2qeZI
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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Lol that's actually hilarious There are certainly possible criticisms, but since they used rigorous measures of diabetes/smoking/obesity and controlled for these in their analysis, this is not one of them Pure tribalism!pic.twitter.com/kuzsa2qeZI
"adjustments". Or magic, as more rigorous epistemologists would admit. Mate, before you bloat yourself up like a smug pufferfish, note that most of us ignore ALL crappy epidemiology, whether it confirms our biases or not.
Lol nope, that's total nonsense. It is statistical manipulation, not magic
Anyway, your discounting of those who have revealed the problems with the substance and PR-idiocy of this latest debasement of science as "pure tribalism" reveals your tawdry cards too clearly.
Uh, she made several factually incorrect statements that you are defending with total gibberish, it is hardly to your credit that all you can do is babble insults at me rather than try to understand the basics of statistical adjustment for confounding variables
There's basic adjustment for confounding variables, and there's statistical voodoo atop the GIGO dumpster fire this study's "dataset" represents. There's no distilling an inherent, platonic truth-signal from pure entropy.
What utter nonsense. They were Cos proportional hazard models with cubic splines, that is fairly standard in such epidemiological research
Here is the study, I'd recommend the "methods" section it's very enlightening https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(18)30135-X/fulltext#seccestitle80 …
It's crucial not to adjust for mediators or their proxies, as explained by @yudapearl below.
If carbohydrates cause CVD via a mediator, e.g. excess insulin production, then diabetes, and arguably energy intake, are proxies, so adjusting for them renders the analysis impotent. 1/pic.twitter.com/B4A0ketuF4
It's also odd that they based the carbohydrate levels solely on baseline and visit 3. What was with with all the other data?
Not at all. As the study states, they only took the FFQ - including the carbohydrate questions - at visits 1 and 3
Oh yes, you're right, but let's say, then, an odd choice not to collect more data when it was possible, especially considering that FFQs are not very reliable. Do you not agree that adjusting for mediator proxies invalidates the analysis?
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