the larger the trial size, the smaller the outcome

I find this a bit surprising. Could there be something else affecting the accuracy of larger trials? Perhaps they are not as careful, or cutting corners somewhere?

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lamename 4 hours ago | parent | next [-]

Maybe. Those could be the case. But ignoring all confounding factors, this phenomenon is possible with numerical experiments alone. One of the meanings of "the Law of Small Numbers".

Basically, the possibility that the small study was underpowered, and just lucky...then the large studies with more power are closer to the truth. https://en.wikipedia.org/wiki/Faulty_generalization

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kadushka 4 hours ago | parent [-]

Sure, could be just lucky. But if there are several successful small studies, and several unsuccessful large ones (no idea if this is the case here), we should probably look for a better explanation.

	▲	svara 3 hours ago \| parent [-]
		It does not require more explanation: publication bias means null results aren't in the literature; do enough small low quality trials and you'll find a big effect sooner or later. Then the supposed big effect attracts attention and ultimately properly designed studies which show no effect.

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hirvi74 4 hours ago | parent | prev [-]

Just my hypothesis, but I wonder if larger sample sizes provide a more diverse population.

A study with 1000 individuals is likely a poor representation of a species of 8.2 billion. I understand that studies try to their best to use a diverse population, but I often question how successful many studies are at this endeavor.

	▲	kadushka 4 hours ago \| parent [-]
		use a diverse population If that's the case, we should question whether different homogeneous population groups respond differently to the substance under test. After all, we don't want to know the "average temperature of patients in a hospital", do we?