Sunday, September 04, 2005
这下造假有根据了
看看下面这个比较耸人听闻但真实可信的消息
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Scientist Says Most Scientific Papers Are Wrong
Posted by Zonk on Tuesday August 30, @06:37PM
from the what-if-his-paper-is-one-of-the-wrong-ones dept.
An anonymous reader writes "According to epidemiologist John Ioannidis, the majority of published scientific papers are wrong.
If Ioannidis's own paper is right, a randomly chosen scientific paper has less than a 50% chance of being true. He also says that many papers may only be accurate measures of the prevailing bias among scientists.
However, a senior editor of a scientific journal says that scientists are already aware of this: 'When I read the literature, I'm not reading it to find proof like a textbook. I'm reading to get ideas. So even if something is wrong with the paper, if they have the kernel of a novel idea, that's something to think about.'"
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这个是原文的出处
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Why Most Published Research Findings Are False
John P. A. Ioannidis
Summary
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.
John P. A. Ioannidis is in the Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece, and Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, Massachusetts, United States of America. E-mail: jioannid@cc.uoi.gr
Competing Interests: The author has declared that no competing interests exist.
Published: August 30, 2005
DOI: 10.1371/journal.pmed.0020124
Copyright: © 2005 John P. A. Ioannidis. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abbreviation: PPV, positive predictive value
Citation: Ioannidis JPA (2005) Why Most Published Research Findings Are False. PLoS Med 2(8): e124
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想起前几天同学在重复师兄东西的时候遇到的困惑
没办法
现实就是如此
－－－－－－－－－－－－－－－－－－－－－－－－
Scientist Says Most Scientific Papers Are Wrong
Posted by Zonk on Tuesday August 30, @06:37PM
from the what-if-his-paper-is-one-of-the-wrong-ones dept.
An anonymous reader writes "According to epidemiologist John Ioannidis, the majority of published scientific papers are wrong.
If Ioannidis's own paper is right, a randomly chosen scientific paper has less than a 50% chance of being true. He also says that many papers may only be accurate measures of the prevailing bias among scientists.
However, a senior editor of a scientific journal says that scientists are already aware of this: 'When I read the literature, I'm not reading it to find proof like a textbook. I'm reading to get ideas. So even if something is wrong with the paper, if they have the kernel of a novel idea, that's something to think about.'"
－－－－－－－－－－－－－－－－－－－－－－－－－－－－－
这个是原文的出处
－－－－－－－－－－－－－－－－－－－
Why Most Published Research Findings Are False
John P. A. Ioannidis
Summary
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.
John P. A. Ioannidis is in the Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece, and Institute for Clinical Research and Health Policy Studies, Department of Medicine, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, Massachusetts, United States of America. E-mail: jioannid@cc.uoi.gr
Competing Interests: The author has declared that no competing interests exist.
Published: August 30, 2005
DOI: 10.1371/journal.pmed.0020124
Copyright: © 2005 John P. A. Ioannidis. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abbreviation: PPV, positive predictive value
Citation: Ioannidis JPA (2005) Why Most Published Research Findings Are False. PLoS Med 2(8): e124
－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－－
想起前几天同学在重复师兄东西的时候遇到的困惑
没办法
现实就是如此
# posted by long @ 7:53 PM 
