Hard Light Productions Forums
Off-Topic Discussion => General Discussion => Topic started by: General Battuta on May 13, 2012, 11:04:02 pm
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We must stand ever vigilant against the creeping possibility of heuristic bias and systemic error! Empirical investigation depends on it!
Alarming cracks are starting to penetrate deep into the scientific edifice. They threaten the status of science and its value to society. And they cannot be blamed on the usual suspects — inadequate funding, misconduct, political interference, an illiterate public. Their cause is bias, and the threat they pose goes to the heart of research.
Bias is an inescapable element of research, especially in fields such as biomedicine that strive to isolate cause–effect relations in complex systems in which relevant variables and phenomena can never be fully identified or characterized. Yet if biases were random, then multiple studies ought to converge on truth. Evidence is mounting that biases are not random. A Comment in Nature in March reported that researchers at Amgen were able to confirm the results of only six of 53 'landmark studies' in preclinical cancer research (C. G. Begley & L. M. Ellis Nature 483, 531–533; 2012). For more than a decade, and with increasing frequency, scientists and journalists have pointed out similar problems.
Early signs of trouble were appearing by the mid-1990s, when researchers began to document systematic positive bias in clinical trials funded by the pharmaceutical industry. Initially these biases seemed easy to address, and in some ways they offered psychological comfort. The problem, after all, was not with science, but with the poison of the profit motive. It could be countered with strict requirements to disclose conflicts of interest and to report all clinical trials.
Yet closer examination showed that the trouble ran deeper. Science's internal controls on bias were failing, and bias and error were trending in the same direction — towards the pervasive over-selection and over-reporting of false positive results. The problem was most provocatively asserted in a now-famous 2005 paper by John Ioannidis, currently at Stanford University in California: 'Why Most Published Research Findings Are False' (J. P. A. Ioannidis PLoS Med. 2, e124; 2005). Evidence of systematic positive bias was turning up in research ranging from basic to clinical, and on subjects ranging from genetic disease markers to testing of traditional Chinese medical practices.
How can we explain such pervasive bias? Like a magnetic field that pulls iron filings into alignment, a powerful cultural belief is aligning multiple sources of scientific bias in the same direction. The belief is that progress in science means the continual production of positive findings. All involved benefit from positive results, and from the appearance of progress. Scientists are rewarded both intellectually and professionally, science administrators are empowered and the public desire for a better world is answered. The lack of incentives to report negative results, replicate experiments or recognize inconsistencies, ambiguities and uncertainties is widely appreciated — but the necessary cultural change is incredibly difficult to achieve.
Researchers seek to reduce bias through tightly controlled experimental investigations. In doing so, however, they are also moving farther away from the real-world complexity in which scientific results must be applied to solve problems. The consequences of this strategy have become acutely apparent in mouse-model research. The technology to produce unlimited numbers of identical transgenic mice attracts legions of researchers and abundant funding because it allows for controlled, replicable experiments and rigorous hypothesis-testing — the canonical tenets of 'scientific excellence'. But the findings of such research often turn out to be invalid when applied to humans.
“A biased scientific result is no different from a useless one.”
A biased scientific result is no different from a useless one. Neither can be turned into a real-world application. So it is not surprising that the cracks in the edifice are showing up first in the biomedical realm, because research results are constantly put to the practical test of improving human health. Nor is it surprising, even if it is painfully ironic, that some of the most troubling research to document these problems has come from industry, precisely because industry's profits depend on the results of basic biomedical science to help guide drug-development choices.
Scientists rightly extol the capacity of research to self-correct. But the lesson coming from biomedicine is that this self-correction depends not just on competition between researchers, but also on the close ties between science and its application that allow society to push back against biased and useless results.
It would therefore be naive to believe that systematic error is a problem for biomedicine alone. It is likely to be prevalent in any field that seeks to predict the behaviour of complex systems — economics, ecology, environmental science, epidemiology and so on. The cracks will be there, they are just harder to spot because it is harder to test research results through direct technological applications (such as drugs) and straightforward indicators of desired outcomes (such as reduced morbidity and mortality).
Nothing will corrode public trust more than a creeping awareness that scientists are unable to live up to the standards that they have set for themselves. Useful steps to deal with this threat may range from reducing the hype from universities and journals about specific projects, to strengthening collaborations between those involved in fundamental research and those who will put the results to use in the real world. There are no easy solutions. The first step is to face up to the problem — before the cracks undermine the very foundations of science.
The history of science - especially in medicine - is full of false confidence. Radical mastectomy was once seen as the only viable solution to breast cancer - removal not just of the breast but of the lymph nodes beneath, and the pectoral muscle, and, essentially, as much tissue as the surgeon could stomach. When the patient survived (a dicey proposition at best), they were left hollowed out, maimed for life. A rigorous, clear-headed look at the statistics involved would have made it apparent that radical mastectomy was not doing the job. The same phenomenon occurred during the smoking (and lung cancer) booms: motivated cognition clouded a clear empirical connection.
In both cases the errors were corrected. The takeaway here is CONSTANT VIGILANCE
source: nature http://www.nature.com/news/beware-the-creeping-cracks-of-bias-1.10600
p.s. game of thrones was really good tonight and i blew up an uziel and a thanatos in an elemental suit
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The belief is that progress in science means the continual production of positive findings. All involved benefit from positive results, and from the appearance of progress. Scientists are rewarded both intellectually and professionally, science administrators are empowered and the public desire for a better world is answered. The lack of incentives to report negative results, replicate experiments or recognize inconsistencies, ambiguities and uncertainties is widely appreciated — but the necessary cultural change is incredibly difficult to achieve.
And there we have the problem highlighted beautifully.
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Statistical science is in a terrible state to be honest, you can find a 'study' that proves just about anything, and half of them reek of observer bias. There's always going to be a little bias, but, especially in the case of externally initiated studies, it's almost got to spin-doctoring in some areas. I've seen, in the space of a couple of days of each other, two studies that claimed exactly the opposite thing to each other, I think it was about computer games and its psychological impact.
Now, when I see something like that, I don't think "what's the issue with the computer games?', I instead think, 'Whats the issue with the science being used here?'.
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"[NO RELIGION VS. SCIENCE]"
you probably have a lot more to fear from those who do not support the theory of anthropogenic climate change.
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And there we have the problem highlighted beautifully.
I'm unconvinced of this; though they claim the problem isn't funding or illiterate public, the idea that the production of positive results does not impact funding or perception by the public is itself pretty hard to sustain.
Biomedical science is a case in point. Research is pushed entirely by the ability to turn something into a treatment. That requires positive findings. Other things are not funded and other research not done. The sources of bias are not purely internal.
In other words they're biased about bias. Around and around in circles it goes...
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Essentially, welcome back to the biased hamster wheel.
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And there we have the problem highlighted beautifully.
I'm unconvinced of this; though they claim the problem isn't funding or illiterate public, the idea that the production of positive results does not impact funding or perception by the public is itself pretty hard to sustain.
Biomedical science is a case in point. Research is pushed entirely by the ability to turn something into a treatment. That requires positive findings. Other things are not funded and other research not done. The sources of bias are not purely internal.
In other words they're biased about bias. Around and around in circles it goes...
I'm reading the section I pulled out and your response, and I'm really not seeing any difference. The Nature editorial claims in part that positive bias because of funding and perception is a major problem...
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Out of curiosity, how do these "biased" scientific fields perform their experiments? Do they perform them in series or in parallel? And if in series, do they perform it on the same materials/subjects they used last time or do they start fresh?
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I don't think these problems can be isolated to specific fields, though I think that some fields (physics, for instance) benefit from their focus on disconfirmation as the jackpot.
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With the exception of string theory :P :poeface:
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Everyone would love to disconfirm string theory; the problem seems to be finding a realistic way to do so.
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The problem is that SCIENCE is done by PEOPLE. Filthy apes with meat brains. :)
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I'm reading the section I pulled out and your response, and I'm really not seeing any difference. The Nature editorial claims in part that positive bias because of funding and perception is a major problem...
*cough*
Second line of the editorial. If their opening statement is not trustworthy...
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Everyone would love to disconfirm string theory; the problem seems to be finding a realistic way to do so.
While it's an interesting theory, it's completely untestable on the current technology level, and I'm not even sure if we already have mathematic tools for it. AFAIK, it borders on being completely abstract, due to downright alien mathematics required. Right now, not going insane from just thinking about it is an achievement. :)
But in general, you've got the point. You shouldn't become to attached to your physics theories, because everybody is working day and night to find a crack in them, and there's a big chance they'll find one.
On the other hand, remember that physics may be threatened by some scientists' reluctance to accept the fact that an old, seemingly proven theory might be wrong. I don't know how much of a problem this is (hopefully it's mostly a thing of the past by now), but it'd be in line with natural human behavior.
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I'm reading the section I pulled out and your response, and I'm really not seeing any difference. The Nature editorial claims in part that positive bias because of funding and perception is a major problem...
*cough*
Second line of the editorial. If their opening statement is not trustworthy...
...go figure. You'd think Nature's editors of all people could write an editorial that is internally consistent =)
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some scientists' reluctance to accept the fact that an old, seemingly proven theory might be wrong.
The one guy who doesn't want to be the next Einstein.
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There was a recent article in Scientific American, I think, about the consequences of the publish-or-die mentality resulting in a lot of people publishing garbage about experiments they never ran and results they never got. Not bias, out-and-out lying. That, too, should probably be considered.
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On the other hand, remember that physics may be threatened by some scientists' reluctance to accept the fact that an old, seemingly proven theory might be wrong.
Given that physics in particular has no problem with giving as much credit to those who disprove a theory as to those who prove one, this is less of an issue than you think.
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Soft sciences are the worst. Specially the ones who mix psychological analysis with "MRI" tests.
Whenever I want to laugh out loudly, I just have to pull the most recent study on these fields.
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Soft sciences are the worst. Specially the ones who mix psychological analysis with "MRI" tests.
Whenever I want to laugh out loudly, I just have to pull the most recent study on these fields.
Oh you (http://i.somethingawful.com/forumsystem/emoticons/emot-allears.gif)