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10.1186/s13643-015-0004-8 http://scihub22266oqcxt.onion/10.1186/s13643-015-0004-8 C4460648!4460648!25875027     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Syst+Rev 2015 ; 4 (ä): ä Nephropedia Template TP {{tp|p=25875027|t=2015. Quantifying the risk of error when interpreting funnel plots |pdf=|usr=}}{{25875027}} gab.com Text Quantifying the risk of error when interpreting funnel plots JO: Syst Rev http://www.kidney.de/pget.php?&tw=1&pmid=25875027 #FOAvip Background: Funnel plots are widely used to investigate possible publication bias in meta-analyses. There has, however, been little formal assessment of whether a visual inspection of a funnel plot is sufficient to identify publication bias. Methods: Visual assessment of bias in a funnel plot is quantified using two new statistics: the Imbalance and the Asymmetry Distance, both intended to replicate how a funnel plot is typically assessed. A simulation study was performed to assess the performance of these two statistics for identifying publication bias. Results: The two statistics both have high type I error and low statistical power, unless the number of studies in the meta-analysis is very large. These results suggest that visual inspection of a funnel plot is unlikely to lead to a valid assessment of publication bias. Conclusions: In most systematic reviews, visual inspection of a funnel plot may give a misleading impression of the presence or absence of publication bias. Formal statistical tests for bias should generally be preferred. Electronic supplementary material: The online version of this article (doi:10.1186/s13643-015-0004-8) contains supplementary material, which is available to authorized users. Twit Text FOAVip Quantifying the risk of error when interpreting funnel plots ????Syst Rev http://www.kidney.de/pget.php?&tw=1&pmid=25875027 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25875027 #FOAvip English Wikipedia <ref>{{Cite pmid|25875027}}</ref> Quantifying the risk of error when interpreting funnel plots #MMPMID25875027 Simmonds M Syst Rev 2015[]; 4 (ä): ä PMID25875027show ga Background: Funnel plots are widely used to investigate possible publication bias in meta-analyses. There has, however, been little formal assessment of whether a visual inspection of a funnel plot is sufficient to identify publication bias. Methods: Visual assessment of bias in a funnel plot is quantified using two new statistics: the Imbalance and the Asymmetry Distance, both intended to replicate how a funnel plot is typically assessed. A simulation study was performed to assess the performance of these two statistics for identifying publication bias. Results: The two statistics both have high type I error and low statistical power, unless the number of studies in the meta-analysis is very large. These results suggest that visual inspection of a funnel plot is unlikely to lead to a valid assessment of publication bias. Conclusions: In most systematic reviews, visual inspection of a funnel plot may give a misleading impression of the presence or absence of publication bias. Formal statistical tests for bias should generally be preferred. Electronic supplementary material: The online version of this article (doi:10.1186/s13643-015-0004-8) contains supplementary material, which is available to authorized users. äQuantifying the risk of error when interpreting funnel plots (epmc).pdf DeepDyve Pubget Overpricing