From: mha23x@gmail.com   
      
   Why Most Published Research Findings Are False    
      
      
   PLoS Med. 2005 Aug; 2(8): e124.    
   Published online 2005 Aug 30. doi:  10.1371/journal.pmed.0020124    
   PMCID: PMC1182327    
      
   Why Most Published Research Findings Are False    
      
   John P. A. Ioannidis    
   Author information â–º Copyright and License information â–º   
   See "Minimizing Mistakes and Embracing Uncertainty" , e272.    
   See "Truth, Probability, and Frameworks" in volume 2, e361.    
   See "Power, Reliability, and Heterogeneous Results" in volume 2, e386.    
   See "The Clinical Interpretation of Research" in volume 2, e395.    
   See "Author's Reply" in volume 2, e398.    
   See "Why Most Published Research Findings Are False: Problems in the Analysis"   
   in volume 4, e168.    
   See "Why Most Published Research Findings Are False: Author's Reply to Goodman   
   and Greenland" in volume 4, e215.    
   See "Why Current Publication Practices May Distort Science" in volume 5, e201.    
   This article has been cited by other articles in PMC.    
      
   Abstract    
   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.    
      
   Published research findings are sometimes refuted by subsequent evidence, with   
   ensuing confusion and disappointment. Refutation and controversy is seen   
   across the range of research designs, from clinical trials and traditional   
   epidemiological studies [1†  
   “3] to the most modern molecular research [4,5]. There is increasing concern   
   that in modern research, false findings may be the majority or even the vast   
   majority of published research claims [6–8]. However, this should not be   
   surprising. It can be    
   proven that most claimed research findings are false. Here I will examine the   
   key factors that influence this problem and some corollaries thereof.    
      
      
   Modeling the Framework for False Positive Findings    
      
      
      
      
   Read More:    
      
   http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/?report=classic    
      
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