Why Most Published Research Findings Are False
John P. A. Ioannidis
Erstpublikation in: PLoS Med 2(8): e124.
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 fi ndings 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.Von John P. A. Ioannidis im Text Why Most Published Research Findings Are False (2005)
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.Von John P. A. Ioannidis im Text Why Most Published Research Findings Are False (2005)
Dieser wissenschaftliche Zeitschriftenartikel erwähnt ...
KB IB clear
|Effektstärkeeffect size, Metaanalysemeta-analysis, Signifikanz, Simulation, Statistikstatistics, type I errortype I error, type II errortype II error|
Volltext dieses Dokuments
|Why Most Published Research Findings Are False: Artikel als Volltext (: , 250 kByte; : 2020-10-28)|