Slashdot Mirror
Most Science Studies Tainted by Sloppy Analysis
mlimber writes "The Wall Street Journal has a sobering piece describing the research of medical scholar John Ioannidis, who showed that in many peer-reviewed research papers 'most published research findings are wrong.' The article continues: 'These flawed findings, for the most part, stem not from fraud or formal misconduct, but from more mundane misbehavior: miscalculation, poor study design or self-serving data analysis. [...] To root out mistakes, scientists rely on each other to be vigilant. Even so, findings too rarely are checked by others or independently replicated. Retractions, while more common, are still relatively infrequent. Findings that have been refuted can linger in the scientific literature for years to be cited unwittingly by other researchers, compounding the errors.'"
They can study my taint anytime they want. /Karma
Living With a Nerd
And they are routinely reported sensationalistically in the media, and most of you people who are reading this right now swallow it all hook and sinker.
Are you adequate?
Quo usque tandem abutere, Nimbus, patientia nostra?
all i can say is "duh!". Everybody, being under pressure of "you have to publish", publish whatever they can. Sad but true
It is way off the base to say that "most published research findings are wrong". It is often the case that data analysis and interpretation for particular aspects of a research project (like 1-2 figures in a 7 figure paper) are up for vigorous debate. The scientific community can, in the long run, converge on very robust ideas, and drop those that are flimsy. To misleadingly imply that most research is wrong, which is exactly what the post suggests, is just poor interpretation of flimsy data, ironically.
It should be noted that "medical research" (epidemiology, clinical studies etc...) is very different from basic research (mechanisms, pathways, etc...) and the threshold for acceptance in journals that cover basic research is much higher than that for medical journals. i.e. There is significantly higher oversight and peer review criticism over basic research than there is medical research and the two fields should not be confused.
Visit Jonesblog and say hello.
How can we even trust this study?
After all, studies show that most studies are wrong.
How do we know the study that shows that most studies are tainted isn't tainted?
According to my research, most studies involve about 84% error rate due to flawed statistical analysis caused by people pulling statistics out of their arse. The other 16% are flawed due to NOT actually pulling statistics out of their arse.
Agent K: A *person* is smart. People are dumb, stupid, panicky animals, and you know it.
This was certainly true in my experience. When I did a review of mathematical methods in my area a while back, most papers had basic calculation errors, missing information that made reproducing the work difficult or impossible, and they all used carefully selected examples to show their work in the best light.
And one of the first rules is, "Never take a single study as proof of anything! Wait till the results are replicated before you even think of moving to a conclusion."
The major problem is really poor reporting on science research. The news media routinely blazon some **NEW * Scientific * Discovery!!!**. Then you read the story and somewhere around the 10th paragraph you might see that this is based on only one study - and oftentimes even before peer review.
Every scientists knows this. It's a shame the public doesn't. They wouldn't worry so much.
The secret is out! Investigators are looking into whether or not millions of scientists have been using modified versions of SCIgen for their work. The FBI and Department of Termpaper Security have acknowledged the investigation but declined to speculate on the alleged ties between SCIgen and grammar terrorists citing a new law just passed by pResident Bush which allows warrantless underwear tapping.
Authorities are also investigating the connections between Malda, Bush Laden, Bill Gates, Dvorak and Borat SCIgen is a program that generates random Computer Science research papers, including graphs, figures, and citations. It uses a hand-written context-free grammar to form all elements of the papers. Our aim here is to maximize amusement, rather than coherence.
Infiltrated dot Net
/. commentors commenting on sloppy submission about sloppy analysis
pot, meet kettle
His work seems to focus on population genetics and epidemiology, which is notorious for having unreproducible claims due to a combination of uncorrected multiple testing, publication bias and statistical incompetence. This "gender and genes" is a perfect example: someone does a study, finds nothing, slices and dices the data until he gets p = 0.04 for females or Asians or smokers and publishes his breakthrough finding. I'd have been surprised if he hadn't found almost all of those to be wrong.
If you look at more in-vitro molecular biology and biochemistry work, I doubt if nearly as high a percentage of it is clearly "wrong", although quite a bit of it is worthless.
What I'm listening to now on Pandora...
I just read the article and checked his statistics. He did his numbers wrong.
"We all know..." What are you basing this on??? As a postdoc, I've committed myself to a massive amount of work and I'm certainly not doing it for pay (which is meager), but a LITTLE amount of respect would be nice. I've published a few studies and it was incredibly hard work to do the kind of careful science that gets published. A small amount of scandals and people like you who swallow any sensationalist piece of news out there really cast things in an unfair light. I encourage you to read more scientific literature and actually try and understand how the scientific process works. Do you really think we live in the kind of technological age as we do in spite of "a good portion of all studies" being "bogus" or "based on nothing"? I find this incredibly insulting.
I am not a scientist.
That being said, it's my understanding that most scientists work off of grants, and those grants fund novel research. Replicating results is of obvious importance in validating those results, but doing so seems at odds with the funding mechanisms that are the reality for what I would believe to be most researchers.
Are researchers supposed to replicate the experiments of others in their spare time and on their own dime?
(As rhetorical as that might have sounded, I actually welcome those with first-hand experience to respond to it)
Oh, say does that Star-Spangled Banner entwine / The myrtle of Venus with Bacchus's vine?
You'd think a postdoc would have known this.
And I wasn't disappointed. You also managed to please me with your inclusion of the bogus "The Great Global Warming Swindle", "Global Cooling", and conspiracy theories. Excellent!
As an interesting aside, I thought that this argument had been dropped because it was a little too easy to shoot down: The interesting thing is that, despite warming temperatures, the oceans are holding more CO2 than before (which lowers their pH level as CO2 + H20 = C2H03, carbonic acid). This is possible because increasing the partial pressure of CO2 in the atmosphere (as we've done significantly) more than counteracts the decreased solubility due to temperature rises. It's possible that in the past this was a factor (although you should read up on those time courses and realize that your 800 year figure is also bogus), but it's clearly not true today. Global warming theories aren't based on correlations, they're based on fundamental principles of science.Ben Hocking
Need a professional organizer?
TFA
Since the criterion is that the claim is published, someone had to find the study new and interesting. Most new ideas are going to be wrong, especially true the more significant it is. After all, how many crackpot theories were postulated between Newtonian and Relativistic physics? On the other hand, most things easily verifiable, etc, are too obvious to me considered new and interesting. Note, while I find this interesting, I did not come up with this idea. Some economists published a similar study over a year ago postulating this as a reason. Of course, it's probably wrong.
Your ad here. Ask me how!
So, is what you're basically saying is that this study was tainted by sloppy analysis?
Ben Hocking
Need a professional organizer?
It's psychosomatic. You need a lobotomy. I'll get a saw.
It is fairly common knowledge that 3 things factor into tenure (in this order): (1) being published (2) bringing funding into the university and (3) teaching.
...
1. A good number to shoot for is 15 journal articles in your first 6 years. If you don't have tenure in 6 years chances are you are never going to get it. The point of being published is to get the name of the university out.
2. Should be self-explanatory. You need to bring in $$$ to the university. The more you bring, the more profitable you are and the more they need to keep you around. But publishing is still more important.
3. Teaching, while as students we all feel is important, is actually the least important thing towards tenure. A mediocre or even bad teacher who writes papers (that get accepted by excellent journals) at a rapid pace will get tenure where an excellent teacher who can't write for the life of him will not. This is why you often see people from industry teaching. They teach for the love, tenured professors are there for the research and for the higher level teaching (where it is more a relation of facts, not an educational process).
The 'sloppy analysis' referred to is not 'fraud' as you cite. There is a difference between fraud and sloppy analysis. The rush to put out papers (between 2 and three a year, by this guide, for tenure) causes some slop to occur. As a reference, I've been working on a paper with my advisor and a (yet-to-be-tenured) professor for almost a year already, and we are just submitting it to a major journal. And the paper is based mostly off of my thesis work completed a year ago! A good paper and good research takes time. But please, do not mistake sloppy analysis for fraud. Mistakes are one thing, deception entirely another.
SOURCE: Advice to rocket scientists: A Career Survival Guide for Scientists and Engineers. Dr. Jim Longuski, published by the AIAA in 2004. But again, this is fairly common knowlege and can be found anywhere you look. As a postdoc (I am too) I'm suprised you didn't know
People need to realise that a lot of those calling themselves scientists are not really scientists at all. They don't apply the scientific method. They massage data regularly. They misapply statistics constantly. They don't subject their theories to falisfiability. They waffle, hand wave, engage in rhetoric, and generally do just about everything except an honest to goodness, old fashioned solid, scientific experiment.
Feynman spotted them over 30 years ago. He called them Cargo Cult Scientists. They put on the appearance of science, but have none of its substance. They give a good performance, like an actor playing a scientists on TV. They wear the clothes, speak the language, seemingly apply the methods. But it's all empty. There's no rigor. There's no insight. There's no real testing going on. It's all just people waving around graphs, and lines, and their qualifications, and formulae they don't understand, to support the theories they want to be true, regardless of whether they are true or not.
It's because in this day and age, you can't be a witchdoctor. You can't appeal to spirits, or gods, or karma, or any of the other philosophical reason thrown up in past ages. We live in "The Age of Reason", and people expect things to be proven to them "scientifically". So all the people who in the past would have risen high by browbeating, appealing to authority and writing great prose, are forced to dress themselves up in white coats and go through the motions of an experiment before they proclaim their great revelations to the world. The experiments however, are just as empty as all the old techniques, and bear only superficial relation to actual science.
Personally, I think it's gotten worse over the last 30 years. The unwillingness of actual scientific communities to challenge the misapplication of their methods by unscientific ones has lead to a dilution of the authority of science as a whole. Under the current regime any half baked psychiatrists can show pictures to 20 undergraduates, record a few squiggles on an MRI, run the numbers through R over and over until he gets what he wants, and proclaim to the world just about whatever he likes, and still be called a scientist! No wonder it's all too easy for the Intelligent Design movement to pose as "real science". Just look at how low the threshold for real science is.
There's only one way to deal with Cargo Cult Scientists. You have to call them out. You have to show how flimsy and false their supposed science really is. You also need to learn all the old rhetorical techniques, because faced with someone who actually knows what they're doing, the Cargo Culter will fall back to very old and time honored methods which enable him to win from a weak or false position. I think the real scientific community owes it to itself to show up these charlatans for what they really are, Con men. If they don't, science will just become more diluted in the long run until the public regards it in the same way it regards homeopathy.
May the Maths Be with you!
Universities are pumping out PhD's at a prodigious rate. As a manager of R&D, I've interviewed and hired more than my share. Virtually all say they want to do research.
Here's my problem. Only a fraction (I'm guessing 1 out of 5) are actually capable of doing good research. The rest are competent employees for developing other people's research into useful products, but aren't terribly original thinkers, nor show a lot of initiative, nor show the rigour and clarity of thought one wants to see in a researcher.
Frankly, when I "unleash" employees on open-ended problems without much guidance, the majority soon begin to flounder.
There is nothing wrong with getting advanced degrees, but many then feel they are obliged to do original research when in fact they really aren't up to it. This may be one reason why the quality of papers isn't where it should be.
Well, of course you can trust it, since somebody can verify this independantly. ;)
[Speaking to self...] .... this...
A scientific study published that most scientific studies are wrong... therefore there is a good change of it being wrong.... Which means that most scientific studies are right... But if most studies are right then this one is also right... which means...
c.. an.. t take
[Head explodes]
I think the majority of working scientists don't "know" this and won't believe it either.
Personally, I think it's true. Between publish-or-perish, financial conflicts of interest, and various political and social movements trying to influence science, a lot of published science is worthless.
However, there's a difference between believing that and actually showing that. Anybody wanting to fix that needs clear and convincing proof first.
This guy's main beef appears to be with medical studies and other sciences which rely heavily on statistics (sociology, psychology and the other wannabe-sciences). This is not surprising, to be honest. Statistical analysis isn't difficult, but I've known many social science students. They consider statistics to be extremely advanced and have no other mathematical background. As a result, they don't have a very deep understanding of how to mathematically model a system. Naturally, this will lead to bogus conclusions and incompetent analysis work. Medicine has a similar problem, albeit on a smaller scale. Most of the time, statistical analysis will yield correlations, but they won't tell you anything about the mechanism behind what you're seeing, which is what's important in science.
I'd expect the rate of error for physics experiments to be much lower than that of, say, sociology.
After all, studies show that most studies are wrong.
Clever.
The fact is, good science is hard work. In fact, it is damn hard work, requiring not only a supremely keen intellect but a very high tolerance for tedium, great attention to detail, and usually a big fat wad of cash. Also, it requires a profound lack of ego (and the ability to cope with failure and keep trying), given that a trememdous amount of effort could (and frequently does) wind up being completely discounted by a peer-review or another study.
The endeavor of scientific research obviously provides us tremendous benefits, and is furthering the evolution of our species at a blindingly fast rate (depending on how you look at it, of course). It is very important, very hard, and very expensive.
There are many, many people who would like to be scientists but really don't have the brain for it (as I stated above, it isn't just intelligence that matters). Unfortunately, a lot of them wind up doing research anyway, and they cause problems. Hopefully there are enough good scientists with enough funding to clean up their mess.
I won't analyze again.
As copyright owner of this comment, I authorize everyone to defeat any technological measure which limits access to it.
The Wall Street Journal headline is a tautology. (Note that he's not talking about scientific misconduct, only honest mistakes, incorrect analysis or experimental design which could be improved.)
There are almost no areas of science we're "done" with. The most recent paper on a subject almost always points out where previous papers have gone wrong. Thus, the previous papers have some mistake such as a miscalculation, poor design or incomplete analysis. If you pick any paper published in a peer reviewed journal this month, there's a very high probability that at some point in the future it will be amended or improved by some other paper.
What Ioannidis *has* shown in his recent reports is that in genetics, not enough people are publishing on the same subjects. There are not enough "other papers" out there to check on the previous ones. The result is that papers which in other fields would be recognized as needing improvement are instead treated as the final word.
>According to the scientists
According to the scientists, the program misrepresented what they said.
>the concept of CO2 warming was a fairly small area of research that wasn't taken very seriously
On the contrary, it goes back to Arrhenius and is generally agreed to be the reason the oceans aren't frozen over. The existence of a "greenhouse" effect was in science textbooks decades ago.
>CO2 levels rose about 800 years AFTER the temperature rose.
After the temperature BEGAN to rise. Temperature and CO2 feed on each other in a positive feedback cycle. The Milankovitch cycles, by themselves, aren't enough to account for the temperature swings in the geological record. There needs to be some mechanism that amplifies the temperature swings, and CO2 accounts for it.
That positive feedback implies some important things for making policy. In particular, it means warming will go further than you'd expect -- CO2 production leads to more CO2 production, rising temperatures cause temperature to go up further.
and
Coder's Stone: The programming language quick ref for iPad
MOD PARENT UP!!! Excellent contribution to the discussion!
:: cough ::" You know something
is wrong when even first posters complain about accuracy.
The media often contributes by being dishonest and over-interpreting results.
Most "scientific" papers aren't really scientific. The first clue is that they are poorly written, suggesting that the writers want to hide their poor contribution behind bad expression.
Slashdot editors often are fooled by "junk science", I notice. For example, this article was fraudulent in my opinion: Imaging Breakthrough "Sees" Lung Disease.
The Slashdot article The Car That Makes Its Own Fuel [slashdot.org] has a +5 moderated First Post that expresses the consensus of the comments on that story: "first post to call bullshit!
The Slashdot article Hydrogen Won't Save Our Economy said that water was rare. That's a stretch considering most of the surface of the planet is covered with deep water. Maybe Slashdot editors had never heard of the Pacific ocean. Then there's that small pond called the North and South Atlantic ocean.
I've come to the conclusion that most laypeople are incapable of reading scientific literature. The usual response when I show a paper to someone is "well, I almost understand the title". The solution, then, is to make the papers more accessible. But do that, and peer reviewers complain about the wording and "scholarly writing" (I tried). Given the choice of audiences, it makes more sense to side with other scientists, I'm afraid.
If I had the patience, I'd write two versions of each one of my papers, but that's a lot of extra effort when most people won't bother to read them anyway.
No, but in scientific fields if something is worth a lot scientifically it will get cited.
Please, for the good of Humanity, vote Obama.
Putting aside for a moment the question of whether Genetic Association Studies - the focus of the research paper - are representative of "Most Science", the article does not say the analysis is invariably sloppy, it says it is often mistaken. For genetic association studies, this is not surprising, since it is very difficult to publish a negative result. So, small studies that show a statistically significant relationship are published, but small studies showing no relationship are not. Then, when larger studies are done, the small studies that had the "significant" relationship because of a fortunate or unfortunate set of samples is not confirmed. Indeed, this is what the research article points out; if your threshold for statistical significance is 0.05, then you will report that a chance relationship is significant once in 20 experiments. But, if you can't publish the 19 negative experiments, then lots of chance results get published.
But Dr. Ioannidis has a very narrow definition of science - he only includes statistical studies that use p 0.05 as a threshold for significance. There are, of course, lots of papers that do not show p-values - the purification of a protein, the determination of a genome sequence, the identification of a new fundamental particle. In many cases, p-values are not provided because they are not considered informative - something that happens when the p-value is much much much less than 0.05 (I like my p-values less than Avagadro's constant. With that p-valuep, I think most of my results are correct.)
And, of course, the WSJ misses all of this. The point of the research paper is that you can do everything right, and still be mislead with marginal p-values (0.05). Not sloppy, just not significant enough. We could, of course, require more stringent values, but then we would miss the genuinely rare, but important results.
As the research article points out, results that are reproducible are, in fact, quite likely to be correct. It is perhaps useful to distinguish between science as a paper and science as a process. Most results that stand up to scientific scrutiny over a period of years (that any one cares enough about to validate), are (probably) correct. In some disciplines, which rely heavily on modest thresholds for statistical significance, many results cannot be confirmed.
I have worked in a biotech / pharmaceutical environment for over five years now, and I don't trust the average medical researcher or biologist to accurately calculate the weight of a kilogram of stuff. I would say that their data analysis is habitually poor, if I were not convinced that it is actually habitually awful.
I have been trying to change this for five years. My success in this has been such that it contributed strongly to my recent decision to start searching for another job. The reality is that biomedical researchers simply do not believe in doing mathematical analysis of data properly. They consider it an eccentric habit, forgivable but socially objectionable, like smoking. By common consensus, it is considered much too complicated to expect that any of them can be expected to understand. Your average biologist is innumerate to the nth degree, and proud of it.
I blame their education, which seems to stress naive and antediluvian (excuse the word) analysis practices, if at all. I have seen course materials which in their expression of basic mathematical formulas, betrayed that they had been left unchanged since the days when people used slide rules and logarithmic tables for calculations. Most of their other training is strictly qualitatively, not quantitatively, and focussed more on memorizing that on understanding.
If necessary, they will find a crutch to help themselves to stumble along: Find a paper that defines a formula that looks relevant, and then fill in the numbers. They would not bother doing their own analysis, or trying to understand how the calculation works or whether it is relevant at all. The notion that a good statistical analysis of mathematical modeling can actually contribute to the scientific understanding of an issue, is well beyond most of them.
I am frankly, sick and tired of their attitude, and I still have to work with these people every day. And in my experience, my colleagues are actually better than most. I strongly suspect the WSJ is correct on this one.
Before there is consensus on an issue, there is contention. Before contention there is no theory at all. Only at the the consensus phase can a majority of 'scientists' be correct. During the contention phase, there is the old theory that didn't include the new theory or which may in fact preclude the new theory. In both cases, if the new theory is correct, then the old theory was not. At least part of the pile of peer reviewed papers for the old theory can now be viewed as incorrect.
What's interesting is when an old theory that was passed over can sometimes be resurrected and proven correct, often times to the consternation of the consensus.
Exactly. Incidentally, this is also the way that the no-global-warming myth started, too.
Are you adequate?
Pot meet kettle.
Javascript + Nintendo DSi = DSiCade
Some Epidemiological Claims of Sex Differences for Genetic Effects Not Replicated.
This is a *very* small number of claims from a subsection of a single field of one small bit of science. Tarring all of science based on some potentially dubious epidemiology is badly out of line. It would be like claiming that since some spinach has made people sick, all food is unsafe to eat. Absurd.
Epidemiology itself has a bit of a reputation of having a hard time finding really solid effects, partly because the effects that are measured are frequently multi-variate with lots on confounding effects, partly because you need huge numbers to have very much analysis power, partly because such studies are generally more observational then experimental. This guy has published a bunch of papers in the past arguing (and presenting models for) exactly this kind of problem. He comes up with the logical (if rather obvious) suggestions that amongst others: 1. Smaller studies are less likely to be true. 2. Smaller observed effects are less likely to be true. 3. The greater the financial interests there are in the study, the less likely it is to be true. 4. The "hotter" a topic is, the less likely a study is to be true. Largely these are no shit, sherlock kinds of things.
So, to sum up, there are lots of epidemiological claims in published articles out there that might not be right. This represents neither a new idea, nor a meaningful comment on anything but epidemiology.
-Ted
-=-=- Quantum physics - the dreams stuff are made of.
Ben Hocking
Need a professional organizer?
getting a paper published is the very first step in peer review, not the final word.
So yes, this might be a problem, but when other peers review it the problems are likely to get pointed out.
A peer review paper isn't a paper that HAS been peer reviewed, it one that is being peer reviewed.
Yes, I know that war redundant, but people for get to all to often.
Another reminder - Scientist live to disprove hypothesis and theories.
The Kruger Dunning explains most post on
I supplied this story to /., and I'd like to note that the title of the WSJ article is somewhat misleading since the researcher was concerned with medical studies, not science in general. (That is not to say, however, that some of the same problems of non-replication and unintentional data manipulation don't exist in other disciplines. However, one cannot draw conclusions on those fields from this work.) Also the global warming tag, which has now been removed, was not added by me and was inappropriate for the same reason.
That was the title of a NOVA film in 1998.
`Abstract: This video examines the troubling question of scientific fraud: How prevalent is it? Who
commits it? And what happens when the perpetrators are caught? Factors contributing to "bad science"
include sloppy research, personal bias, lack of objectivity, "cooking and trimming", "publish or perish"
pressure, and outright fraud. The limits of peer review and other quality control systems are discussed.'
The results of the study determined that 48% of all published data was fraudulent. The data was trimmed, cooked or outright falsified. Some cases made famous by public exposure were analyzed.
While recieving a lot of lip service from the establishment science, the two government researchers who made the report were reassigned to worthless tasks in isolated areas. One was sent to shuffle papers in Alaska, IIRC. So much for whistle blowers, even government whistle blowers.
In the last 19 years it seems nothing has changed. Besides this latest report how can I tell? Simple. The news is filled with stories of drugs being recalled because they are more dangerous that the problems they are supposed to treat. How would they ever have gotten on the market in the first place if their FDA "studies" weren't rigged? And you don't wonder about the revolving door policy between Pharmaceutical employees and FDA employees? Corporate influence in research is as corrupting as Microsoft influence in ISO standards voting.
What really burns me is that MUCH of our basic research is done at academic institutions by professors funded by government grants, i.e., tax payers. But, thanks to the best congress that money can buy (because most of them have been bought off) OUR research is "monetized" (sold to special interests) for pennies on the dollar. These interests then reap HUGE license profits for decades. To make matters worse, many of the "special interests" are the very academic researchers who were paid to do their work. Having discovered key facts, without reporting them, they resign academia and begin a corporation to capitalize on what we paid them to learn.
IF we had a congress worth what they are paid there would be a law which prohibits recipients of gov grants, or their families relatives, or former business associates to personally benefit from what they learned using that grant money for a period of 15 years. Secondly, the ONLY corporations which should be allowed to receive IP licenses from the gov should be NON-PROFITS, whose board, management or employees cannot include the professor or his family or relatives.
Another thing that this recent study shows is what the NOVA film revealed: Peer-review is worthless for vetting research. Replication is worthless for vetting research. Obviously, personal integrity is also a worthless indicator of research quality.
Running with Linux for over 20 years!