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10.1073/pnas.1618569114 http://scihub22266oqcxt.onion/10.1073/pnas.1618569114 C5389310!5389310!28320937     free     free     free       Proc+Natl+Acad+Sci+U+S+A 2017 ; 114 (14): 3714-9 Nephropedia Template TP {{tp|p=28320937|t=2017. Meta-assessment of bias in science |pdf=|usr=}}{{28320937}} gab.com Text Meta-assessment of bias in science JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=28320937 #FOAvip Science is said to be suffering a reproducibility crisis caused by many biases. How common are these problems, across the wide diversity of research fields? We probed for multiple bias-related patterns in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was on average relatively small. However, we consistently observed that small, early, highly cited studies published in peer-reviewed journals were likely to overestimate effects. We found little evidence that these biases were related to scientific productivity, and we found no difference between biases in male and female researchers. However, a scientist?s early-career status, isolation, and lack of scientific integrity might be significant risk factors for producing unreliable results. Twit Text FOAVip Meta-assessment of bias in science ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=28320937 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28320937 #FOAvip English Wikipedia <ref>{{Cite pmid|28320937}}</ref> Meta-assessment of bias in science #MMPMID28320937 Fanelli D; Costas R; Ioannidis JPA Proc Natl Acad Sci U S A 2017[Apr]; 114 (14): 3714-9 PMID28320937show ga Science is said to be suffering a reproducibility crisis caused by many biases. How common are these problems, across the wide diversity of research fields? We probed for multiple bias-related patterns in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was on average relatively small. However, we consistently observed that small, early, highly cited studies published in peer-reviewed journals were likely to overestimate effects. We found little evidence that these biases were related to scientific productivity, and we found no difference between biases in male and female researchers. However, a scientist?s early-career status, isolation, and lack of scientific integrity might be significant risk factors for producing unreliable results. äMeta-assessment of bias in science (epmc).pdf DeepDyve Pubget Overpricing