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Why Most Published Research Findings Are False
Hugh Pickens writes "Researchers have found that the winner's curse may apply to the publication of scientific papers and that incorrect findings are more likely to end up in print than correct findings. Dr John Ioannidis bases his argument about incorrect research partly on a study of 49 papers on the effectiveness of medical interventions published in leading journals that had been cited by more than 1,000 other scientists, and his finding that, within only a few years, almost a third of the papers had been refuted by other studies. Ioannidis argues that scientific research is so difficult — the sample sizes must be big and the analysis rigorous — that most research may end up being wrong, and the 'hotter' the field, the greater the competition is, and the more likely that published research in top journals could be wrong. Another study earlier this year found that among the studies submitted to the FDA about the effectiveness of antidepressants, almost all of those with positive results were published, whereas very few of those with negative results saw print, although negative results are potentially just as informative as positive (if less exciting)."
Peer review no doubt helps to limit people who intentionally want to cause problems. Sokal's bullshit paper on quantum gravity (see The Sokal Hoax ) made it into print only through a non-peer-reviewed journal. While it is disturbing to think much published scholarship is unreliable, at least it isn't necessarily malicious.
How long until some researcher releases a study showing that Dr. Ioannidis' research findings are themselves wrong?
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Title is wrong. It says that the FDA is corrupt. And that published papers take around 3years to get peer reviewed where the bad ones are removed. What a blatent attack on science generally. Sure paper publishing needs to be reviewed but 'most published research is false' is an outright LIE. 'Most published research' includes all of our basis of scientific knowledge. If most of our theories on biology were wrong really we realistically wouldnt have been able to move forwards into working with genes if we didnt know what a cell did.
At the risk of being modded down to oblivion, I am still curious to how this effects popular theories like global warming. We already has people claiming that the science is wrong and they are generally mocked and ignored because their works are published in major journals. Well, this story seems to indicate that publishing those claims will give them a larger change of it being incorrect.
Anyways, it seems that if you don't tow the line on climate change, there is no room for you anywhere. So where does this leave the accuracy of the claims in light of how common it seems that they can be wrong even when published in a respectable scientific journal. I know the IPCC looked at them, but they didn't validate any of the claims, they only looks at whether or not Humans were the cause (that was their charter and they acknowledged this in their reporting).
I would think that "Publish or Perish" must contribute to a lot of crappy papers getting published. Shovel it out the door, somebody else says it's wrong, write another grant for a study to verify that, shovel that one out the door, rinse, lather, repeat...
For all intensive purposes, "whom" is no longer a word. That begs the question, "who cares"?
Those responsible for refuting the research of the people who have just been refuted, have been refuted.
Basic idea: high-profile journals want papers that are new and exciting. This means that scientists have an incentive to 1) rush their work, 2) choose fields that are popular, and 3) claim that their papers solve more than they actually do. This leads to sloppy, dishonest papers.
I'm not going to judge this paper - I haven't read it thoroughly - but to pair a title like "Why most published research findings are false" to a pretty well-known problem seems itself like an example of problem 3!
News flash! What works in one situation (or for one person) might not work so well in another. Too little research takes the context into account, particularly regarding any research that is human-related, and so it becomes easy to "disprove" prior findings.
My prediction for this thread:
Several people will post about how this validates the TINY, TINY, TINY, number of scientists and LARGE number of completely uneducated "opinion" formers and MASSIVE number of people who think that "belief" is the same as fact.
What they will miss:
This article talks about how things are put out there then invalidated by SUBSEQUENT PUBLISHED RESEARCH, not about how there is a great conspiracy around something being "right" and everyone shouting down those who dare to disagree. Global Warming is something that has consistently been found to be happening and while certain bits have been revised due to subsequent research, most of that research has found that previously incorrect models were in fact too optimistic in their view.
This article doesn't strengthen your misguided, and uneducated, belief that Global Warming isn't real. When even the Republican candidate says its real then its time to let go and become part of the solution.
An Eye for an Eye will make the whole world blind - Gandhi
Many are wrong. This is pretty obvious, and it's also why science works. Eventually, the wrong ones will be replaced with something less wrong, and so on.
SJW n. One who posts facts.
that proves most published research findings are true.
"You'll get nothing, and you'll like it!"
Why is it that a large portion of scientific research today is garbage. Well one very powerful reason, money. I saw this firsthand working at a major university medical center on large scale behavior research projects. The outcomes of our studies directly effected existing and experimental drugs and the drug company representatives were right there alongside the researchers at all levels of the process. Professors received "gifts" and other unofficial incentives from them regularly. I saw at least one study where the results were out and out fabricated so that the results would support the effectiveness of a particular drug for treating a childhood psychiatric disorder. In other cases data was included after the fact or blanks were filled in by clinicians from memory. All practices that are highly unscientific. Many of these studies resulted in drugs and treatments for children that are in use today and based on research that is at best questionable and at worst fraudulent. When there is a profit motive behind science it becomes very difficult for it to remain true science and sadly that is the state of affairs in many fields today.
Scientific research is just that -- research. If it were as easy as doing a couple of experiments, revealing the "truth" and moving on to the next thing, we'd all be living around Alpha Centauri by now. But science is hard and therefore a lot of conclusions are naturally going to be wrong. If that weren't the case then we wouldn't even need any scientific journals -- all we'd need would be newspapers.
Remember the whole "theory of evolution" issue that the creationists keep harping on? "They call it a theory so it must not really be true?" We all know that evolution is just about as "true" as any science gets -- and yet surely there are some portions of the current body of knowledge about evolution that will one day be falsified by later research. That's not a bad thing.
Notable research that has since been thought to be flawed or insufficient: Newtonian physics. Niels Bohr's model of the atom. Gregor Mendel's research into genetics. Einstein's theory of general relativity. Koch's postulates for determining disease causation. Quantum mechanics. And so on.
Breakfast served all day!
Even after reading the article, I'm still not sure if the authors are saying:
A) Given that research has been published, it is more likely to be false than not; or
B) Given that research is false, it is more likely to be published than is the case for true research.
I mean, it says:
So, (Wrong Articles)/(Total Articles) = >=0.5, right?
But the only figures I can find in the same article are:
So.. "most" is now "less than one third"?
I'm somewhat alarmed that The Economist lets people who don't seem to grasp basic statistics write their articles.
Antiquis temporibus, nati tibi similes in rupibus ventosissimis exponebantur ad necem.
Yes I agree - this paper is not about "Most Published Papers" in Science. It is about published papers in the area of therapy effectiveness. Especially those where we do not have a good model. Thus of course about half should be wrong I would guess, as established by later studies. This is statistics in action. When you are looking for high correlations and selecting for the positive, you will will get false ones. As long as this paper's authors could find LATER PUBLISHED RESEARCH showing this stuff was wrong, that is the scientific method. In fact if, say, 98 and 4/100's of papers were shown to be right later, I would smell something in the woodpile.
The meat of the article is the bias about reporting negative results. This is not a secret.
In regard to something like climate research, really it doesn't apply. but if you take the premise, it would generally bolster the 1000's (+) of papers over the years that show consistent effects and generally put more shadow on the couple showing otherwise. It would mean the papers the doubters bring up are wrong with even more percentage, since these are the papers with no validated mechanisms and generally many defects which immediately get pointed out. That is we would expect some wrong or null correlations to pop-up, given this paper and shouldn't put much support to isolated work that is not buttoned down to the max.
How long until some researcher releases a study showing that Dr. Ioannidis' research findings are themselves wrong?
Who needs a study? Simply reading the article shows that he has fallen precisely into the trap that he is complaining about i.e. overstating his results. He forgets one very simple point: not all science is medicine/biology.
As a particle physicist I would strongly disagree with his conclusions, at least as applied to experimental particle physics. It is certainly true that some papers turn out to be wrong but this is rare and usually ends up as a 'big thing' in the field. Outside my field I'd be very surprised if the majority of physics or even chemistry papers turn out to be wrong (but I certainly not a chemist so this is just my impression).
As for medicine I can certainly see that they have a problem. Afterall how many times have we been told "don't eat X/do Y it is bad for you" only later to find out that actually it isn't half as bad as they thought and may even have benefits? Just because a lot of medical research is often flawed does not mean that all of science has the problem on the same scale.
So, Dr. Ioannidis either show us some data from chemistry, maths and physics or stop complaining that all of science has a problem on this scale. From where I stand your evidence points to a problem with bioscience/medical research only.
When did "almost a third..." become "most?"
So, a paper claiming that small sample sizes lead to wrong conclusions is based on analysing a sample of only 49 other papers? The mind boggles with the self-applicability ...
"Global warming does not fall under this. It has been researched, and retested, and re-challenged numerous times.'
On this point you are walking on loose sands. What do you mean retested? You cannot test Global Warming. You can only make observations about it and then form your own opinion based on those facts. You cannot create 2 identical planets ,mess with their CO2 levels and then compare the results. All your data is based on your measurements and conclusions you draw from it. That is where the controversy lies. In order to test the Global Warming theory you need 2 carbon copies of 1900 earth and have only one use massive amounts of carbon fuels and the other next to none. Only then will you truely approach(you cannot mimick everything) how the system works.
And let us not talk about history because that is even more a topic of disputes.
Knowledge is power. Knowledge shared is power lost.
It's important to identify a problem no matter what, but are any of these biases fixable? I would argue that some of them, specifically the bias toward positive results, is not fixable and is inherent to how science works.
To quote one of the articles "...negative results are potentially just as informative as positive results, if not as exciting." But negative results often require much much more verification than positive results, if they can be verified at all, and are limited in how much they can tell you. The antidepressant studies mentioned, a negative result, that the antidepressants did nothing, only tells you that in the patients tested, the doses tested did not give you a noticeable positive result. Publishing a negative result on that would have very limited conclusions. The next year, they could find that doubling the dose was actually effective, making the writeup of the earlier negative result pointless and even more trivial. A waste of time, plus then you've published saying your own product doesn't work.
Negative results get even more pointless in other fields. If someone does a mutagenesis screen for a particular defect in C. elegans, and doesn't find any mutants affecting that, it could be noteworthy, indicating that any genes affecting that process were so vital that when you took one away you didn't get a worm at all, or it could just be luck that genes affecting the process were never mutated, or the researcher didn't do it correctly, or all genes involved were redundant, or some combination. What conclusions could you draw from that? It would be a negative result that would be nigh impossible to tell anything from. Without any positive hits, you could go to the trouble of making sure you did it correctly, but you're not going to make sure every gene got hit at least once, that would be impossible.
In still other cases, a negative result is often retrospectively found to be the fault of the researcher. Who wants to publish something that is basically telling your peers how dumb you are?
There's also that it requires a lot of extra work to make sure it's a negative rather than a null result. Usually when I hit a negative result, my inclination is to see if I did it wrong by repeating the experiment if possible, if it comes up negative again I usually take a different approach, if that also gets a negative result I re-evaluate. I don't ever do all the other supporting experiments that would be needed to convince a reviewer it's a real negative result. If I use an RNAi construct to knock down a gene, and it doesn't do what I'm expecting or anything else interesting, I don't verify the gene is actually knocked down, since that's more effort that would probably be a waste. I'm definitely taking a risk that it's a real result, but it's hard to prove a negative and there's also less motivation to do so.
The limited ability to make positive conclusions about negative results also limits where they could be published. There is a journal for negative results, but a publication there is not something I personally would put on a CV.
So while it is interesting that a bias against negative results may be throwing us off, it's not very usefull knowledge, because I don't see us able to do anything about it.
And you trust that the paper has been seen and deemed correct by a referee. I've been a referee for a couple of Physical Review papers and unfortunately it is indeed rather common that there is too little information in the paper to allow "checking for sign errors" as you call it. So you cannot really trust that the reviewer had enough information to vet the correctness of the paper.
In my case I sent the articles back to the editor with the comment that the authors should first properly explain what they are doing before I can judge the scientific conclusions, together with a long list of ambiguities in the discussion. I'm quite sure though that most referees don't bother since I would say the same about most published papers.
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This latter group are far more prone to different interpretation by different people.
Engineering is the art of compromise.
In order to test the Global Warming theory you need 2 carbon copies of 1900 earth
That wouldn't work, as the copies would be comprised mostly of carbon powder, so the geophysics would be completely different.
You seem to have NO idea at all about what you are saying. Global warming is based on very exact scientific studies, where "faith" is needed only in that one believes that there exists a reality around us that follows some self-consistent laws.
The studies that present exactly the effects that Dr. Ioannidis mentions are the opposing view, those that pretend to disprove the existence of global warming. Scientist, all over the world, are very strongly in agreement that global warming is an indisputable fact.
While Ioannidis, the author of the original work that was discussed here may be correct that a large fraction of a very specific type of clinical research findings, are incorrect, there is no reason to believe (from his published work) that "most published research findings are false". Most of the ones he looked at were not reproduced, but they had well understood limitations. My papers, I can assure you, are only incorrect about 10% of the time.
Science in general isn't about "publishing what is right" but rather creating a network of accountability in the form of methods, ideas, data, procedures, etc. so others can try and reproduce and critique the results. Even if the published results are shown to be incorrect by other studies, this does not mean the system is broken. The scientific process is an iterative, self correcting, one. However, if after many years and many studies, a particular field fails to converge on an accepted baseline conclusions, there is a good chance something is wrong (you may even be doing pseudoscience).
i\hbar\dot{\psi}=\hat{H}\psi
Indeed in my field (a sub-area of computer science) people are usually highly skeptical of any supposedly important new result in the field that was first published in one of the highly prestigious but generalist journals, like Nature or Science. These often end up being, if not outright wrong, at the very least seriously over-extending their claims or the importance of their claims, in a way that would never get them published in a specialized journal filled with an editorial board who were actually experts in the specific area in question.
This is only exacerbated by the fact that, because generalist publications know they don't have expertise in every specialized area on staff, they often ask the authors to suggest potential reviewers of their own papers. Of course, authors are likely to suggest reviewers who they think will like the paper, not the ones who would give it a grilling.
I think the interest of this particular study is not so much that a lot of science turns out to be wrong, but that a lot of the most prestigious publication venues turned out to be wrong more often.
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
Ioannidis wrote a previous article, titled "Why Most Published Research Findings Are False." A very provocative title, one that practically begged the scientific community to read it just to accumulate a laundry list of holes in his argument. A good marketing maneuver. It may or may not be true that most published research findings are false, but the article certainly didn't demonstrate it. Within the context of the discourse he intiated, that would have to be viewed as a kind of willful stupidity, or perhaps marketing brilliance. After all, if the same journal received ten equally well argued articles with titles like "why most research is pretty good," they would still of course prefer to publish his. This truism seques nicely into the new article (on which he is not first author), which is titled, "Why Current Publication Practices May Distort Science." Use of the word "may" is quite helpful here. Does the article live up to its title? It may not be convincing, but it would be even less so without the word "may."
Afterall how many times have we been told "don't eat X/do Y it is bad for you" only later to find out that actually it isn't half as bad as they thought and may even have benefits? Just because a lot of medical research is often flawed does not mean that all of science has the problem on the same scale.
The problem here is that the popular press always report the very latest 'finding' in what is a complex field. Yet we should know that not only in medicine, but in virtually all experimental sciences, a single paper is not sufficient to establish some new profound truth.
Dr Ioannidis' largest problem is that he thinks he has identified a problem. There isn't one. This is how science is supposed to work! We publish methodologies so that the work can be replicated by other teams. Some findings survive futher scrutiny, some don't. The "hotter" the field, the less you are going to rely on the latest single study, no?
So he's found 1/3 of studies were refuted, but later work. Great, they were refuted, what's the problem? And how do we move from that to the conclusion that "most" scientific papers (even outside the hotter fields of bio-medical research) are wrong. And what about looking at outcomes? The advances of medicine even in my lifetime are astounding, this is hardly the result of a system that isn't working!
Better to be despised for too anxious apprehensions, than ruined by too confident a security. --Edmund Burke
The issues on global warming that are in dispute are numerous... we keep hearing predictions from models that have not been proven to have any predictive powers, and they keep getting more alarmist, and the increasingly ridiculous claims that every example of bad weather is a function of global warming. The issue is the "hockey stick" part of the forward feedback loop... that's the claim that because events will create forward feedback, we will hit a point in a few years where it isn't preventable, because even if we never emitted another CO2 gas, the forward feedback would be self sustaining.
Most things in the universe have negative feedback... The issue with global warming is we know that the current models show this forward feedback, but we KNOW that the models are incomplete. Are we missing significant variables that would create a feedback loop? It seems reasonable to wonder if something will happen with the higher CO2 levels that will cause a negative affect on global warming.
The consequences of GW are dire, and it's a real concern. But the scientific credibility is NOT enhanced by the political advocates calling for the same policies that their fellow ideologues called for for different reasons before, the celebrities weighing in, or the silly exaggerated movies.
Theory of evolution has been tested and demonstrated in small areas with smaller organisms. Theory of evolution is also a concept more than a specific theory, making it easier to demonstrate pieces... yes, evolutionary biology shows the process of small organisms... not the same thing.
Increased CO2 -> increased heat, that's the easy claim
Increased heat -> increased CO2 and there is no way of stopping it is the stranger claim
Perhaps we'll see a spread of CO2 absorbing plants move out of tropical areas to other zones as temperatures change, who knows, but there are plenty of areas for negative feedback, and only time will tell.
You said, "So, Dr. Ioannidis either show us some data from chemistry, maths and physics or stop complaining that all of science has a problem on this scale."
I'm sympathetic to the direction you are going, but I don't agree completely.
The problem is due to being able to get extra money by exaggerating claims. The problem is in every area of science, in my experience. If there is no chance to get more money by exaggerating claims, then I agree, the problem seems minimal.
In computing, claims about "Artificial Intelligence" have been extremely exaggerated.
In physics, there are those who claim they may have found a method of cold nuclear fusion. Search for Sonofusion, for example, fusion that is caused by extremely intense ultrasonic sound. Some of those claims are exaggerated, or there are omissions of the limitations.
yes you can.
Numerous independent climatology models (we're talking virtually every accredited university and think tank on earth with enough resources) based on hundreds of thousands of years of data from geological, oceanographic, and ice core samples, run through supercomputers millions of times.
The only ones that "disagree" are tied to oil companies.
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I read a bunch of dental papers recently, and discovered something rather disturbing. A good 90% or more of studies for dental procedures do NOT use any control group. They all say, "we did X and got the expected result." There is no checking whether the procedure is better than other procedures or even doing nothing at all.
Something to think about next time someone you know is told they need wisdom teeth extracted or some orthodontic appliance.
I can't see what is so surprising here. Basically when you do research, you are groping in darkness - after all, it wouldn't really be worth doing if the results were already known, would it? Approaching a new problem is a bit like looking at the notorious elephant through a keyhole; different people will have different guesses as to what it is and most will be wrong, until at some point enough observations are made and you can construct a more complete picture.
When you publish scientific articles you don't claim that "THIS IS THE TRUTH" - you are merely putting forward your opinion and then somebody else comes along and says "No, because ...". And even the articles with the "wrong" results are valuable, because they tell us that this particular interpretation is not the right one. It can take a lot of false turns before you find the right way through a maze, and in fact it tells us something about the generally high quality of research that we are not seeing about 90% wrong results.
[I]f you have 66% of published results being found to be wrong you have a huge problem!
I agree. Just as well that a mere 16% were outright refuted then isn't it? :P
With another 16% shown to have weaker effects than originally reported.
(Ioannidis P A, 'Contradicted and Initially Stronger Effects ...', JAMA 2005;294:218-228.) Moreover,
the study was based on 45 papers, with an intentional selection bias, they were both highly cited and claimed
high efficacy. Now such citeria might address Dr Ioannidis' particular research interests, but they are hardly
representative of the literature over the 13 year period from which they were selected.
Better to be despised for too anxious apprehensions, than ruined by too confident a security. --Edmund Burke