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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.'"
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.
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?
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.
/. 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...
It's not just medical research. The scientific community works like any other community: the greater the implications, the greater the scrutiny, attempts to replicate, etc. The Huang embryonic stem cell study is a great case-in-point: the image-manipulation fraud was uncovered because of the vast number of researchers looking at the micrographs he published. (That sounds familiar, doesn't it: "Many eyes make all bugs shallow.") Global warming has many, many people working on models, taking ice cores, doing other analysis. Of course, the vast majority of published research isn't reported in Science or Nature, and so it doesn't get as much exposure. That's why around here (the University of Wisconsin), it's standard practice that if your work depends on someone else's result, you first replicate her experiment and make sure you get the same result. (If you can't, you write a letter to the appropriate publication making note of your inability to replicate the result.) This means that eventually the mistake gets uncovered, and your research doesn't get burned because someone else has been sloppy.
"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)
You'd think a postdoc would have known this.
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!
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.
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.