It's been definitiely shown since at least 2010 that phenylephrine is useless for this purpose. How in the world did the FDA let the decongestant industry push this drug for 15 years before coming down on it?
The top response is wrong. So of course it was locked and made impossible to downgrade or correct. If this isn't a canonical Stack Overflow example I don't know what is.
IIRC D&D was so directly based on Tolkien that they used the terms "halfling", "goblin", and "magic user" to avoid a fight with the Tolkien Estate over the terms "hobbit", "orc", and "wizard". This article thus makes little sense to me: how many half-elf magic users do you see popping up in medieval history?
GP is probably thinking of "My dad and me"; not sure how far back it goes but I've certainly heard it quite a bit from native speakers. You might hear someone say, "Him and me, we go way back", but that's slightly different; but "Him and I" mixes the subject/object case, which must be wrong (and I've never heard before).
ETA: I generally don't bother "correcting" the grammar "mistakes" that native speakers make (like "My dad and me did X"); but if I think it's pretty clearly a non-native speaker, I'll correct them, because that's what I would want someone to do for me if I were speaking in their language.
> This is known as the curse of dimensionality (the more things you have to vary, the exponentially more combinations you have to test)
Is this really a valid usage of this term? The only definition I am personally familiar with is from machine learning, and it is something totally different.
I think the fundamental problem is that for every claim yielding a positive result there are many more, perhaps infinitely more, related claims yielding negative results.
Positive result claim: the sun comes up in the morning.
Negative result claims: the sun moves sideways in the morning. The sun was always there. The sun peeks up in the morning and immediately goes back down. And so on.
Positive result claim: aspirin is an effective pain reliever.
Negative result claims: eating sawdust is an effective pain reliever. Snorting water is an effective pain reliever. Crystal Healing is an effective pain reliever. Etc.
Because there are so many negative results, it's trivial to construct an experiment which produces one. So why should that be published?
Negative results should be published when people in the community are asking that question, or have a wrong belief in the answer (hence the replication crisis). But if nobody cares about the question, it's hard to argue for why a given negative result would be preferred over any other negative result for purposes of publication.
So let's say I claim that the sun goes in a circle in the sky in the morning. The null hypothesis is that it doesn't do that. Perform experiment. Null hypothesis wins. Write up paper! This is a negative result.
The point is that for every result where the alternative hypothesis wins, there are a massive, if not infinite, number of results where the null hypothesis will win. Are these publishable?
The idea is that some null hypotheses being true is actually interesting because it challenges an assumed belief. From the first paragraph of the article, the immediate feedback from the postdoc's supervisor was 'you did it wrong [because everyone knows that fish do like warmer water]'.
> It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so.
> The idea is that some null hypotheses being true is actually interesting because it challenges an assumed belief.
??? As I had said originally, that's one of the primary situations where a negative result should be published.
But the huge, huge, huge majority of negative results are trivial and uninteresting. Thus the fundamental issue with negative results is that you have to provide rather more compelling justification for why such results should be published.
Yeah, I agree with your first point, but maybe misunderstood your reply? If there's nothing "surprising" about the result, it's not interesting, so not publishable. The article's first example, however, did seem to be surprising to the researcher's community, so it should have been published.
Sure. What I said, or had meant to say, was in reply to people complaining that there was some kind of cartel against negative results. Rather, what we're seeing is just the natural, if unfortunate, response to the basic problem with negative results as a whole. You can't just treat them as the same as positive results: because of their numerosity they require unusual justification for their publication.
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