You keep conflating "didn't show a benefit" with "wasn't statistically significant", but the latter doesn't make a difference in a binary p-value computation.
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And your idea of "number wasn't corrected properly" means "awful study" is probably only slightly correlating in reality. I've read a 5-digit number of studies, and I find such mistakes in the majority of them, at every level of clinical quality.
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Replying to @EduEngineer @K_Sheldrick
Yes as I said there are a lot of awful studies. This one is particularly worthless tho, for a number of reasons not limited to the one that you want to ignore for some reason
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Replying to @GidMK @K_Sheldrick
I'm not ignoring it. I stated that it was worth contacting the author and figuring it out, but before that step, it's not a reason to suggest "worthless".
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Replying to @EduEngineer @K_Sheldrick
That's one element of quality. It's not even the only thing that I pointed out in this thread. Other issues are the lack of reporting of potential confounders, the inadequate control group, the lack of reporting generally, the contradictions btwn pre-reg and study...
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Replying to @GidMK @K_Sheldrick
Unless there is a reason to believe confounders skew one direction, magically, missed confounders are understood not to have a significant effect on such computed p-values. In fact, that's the point of a p-value: it only asks the question of whether the results happen at random.
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Replying to @EduEngineer @K_Sheldrick
By definition a confounder skews in one direction, otherwise it does not confound the relationship and is not a confounder
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Replying to @GidMK @K_Sheldrick
A confounder skews in one direction *internally* to a single study, but those wash out at high numbers of studies/coin flips. What you need are global confounders to make the argument.
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Replying to @GidMK @K_Sheldrick
It's provably correct. May I invite you to walk through the math with me on camera?
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It has very little to do with maths actually. The maths of meta-analysis is really quite simple, it's just a weighted average, if the included studies all make the same errors in terms of confounding than by definition the weighted average will also have this error
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