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
You believe their adjustments are that perfect? LOL
Man, the number of people responding to this who completely misunderstand statistical adjustment is both funny and terribly sad
I understand they're an art, not a science. If they're relying on other poor epidemiology, may not even get to art.
You misunderstand. And this study used fairly standard methodologyhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017459/ …
Adjusting for confounders is not perfect. You're adjusting bad data using other bad data.
Unless you are attacking their data collection, that is not accurate. The main issue with controlling for confounding variables is residual confounding, which is not what the tweets were about at all
And yes, their data collection was also farcically bad.
Which points of data collection do you have an issue with, specifically?
That is untrue. It was somewhat above starvation level. And it is unsurprising in a study of atherosclerosis that calorie intake would be low, the real issue would be if it differed significantly across groups, which it did not
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