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10.1371/journal.pone.0145580 http://scihub22266oqcxt.onion/10.1371/journal.pone.0145580 C4689383!4689383!26697876     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+One 2015 ; 10 (12): ä Nephropedia Template TP {{tp|p=26697876|t=2015. The Missing Medians: Exclusion of Ordinal Data from Meta-Analyses |pdf=|usr=}}{{26697876}} gab.com Text The Missing Medians: Exclusion of Ordinal Data from Meta-Analyses JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=26697876 #FOAvip Background: Meta-analyses are considered the gold standard of evidence-based health care, and are used to guide clinical decisions and health policy. A major limitation of current meta-analysis techniques is their inability to pool ordinal data. Our objectives were to determine the extent of this problem in the context of neurological rating scales and to provide a solution. Methods: Using an existing database of clinical trials of oral neuroprotective therapies, we identified the 6 most commonly used clinical rating scales and recorded how data from these scales were reported and analysed. We then identified systematic reviews of studies that used these scales (via the Cochrane database) and recorded the meta-analytic techniques used. Finally, we identified a statistical technique for calculating a common language effect size measure for ordinal data. Results: We identified 103 studies, with 128 instances of the 6 clinical scales being reported. The majority? 80%?reported means alone for central tendency, with only 13% reporting medians. In analysis, 40% of studies used parametric statistics alone, 34% of studies employed non-parametric analysis, and 26% did not include or specify analysis. Of the 60 systematic reviews identified that included meta-analysis, 88% used mean difference and 22% employed difference in proportions; none included rank-based analysis. We propose the use of a rank-based generalised odds ratio (WMW GenOR) as an assumption-free effect size measure that is easy to compute and can be readily combined in meta-analysis. Conclusion: There is wide scope for improvement in the reporting and analysis of ordinal data in the literature. We hope that adoption of the WMW GenOR will have the dual effect of improving the reporting of data in individual studies while also increasing the inclusivity (and therefore validity) of meta-analyses. Twit Text FOAVip The Missing Medians: Exclusion of Ordinal Data from Meta-Analyses ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=26697876 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26697876 #FOAvip English Wikipedia <ref>{{Cite pmid|26697876}}</ref> The Missing Medians: Exclusion of Ordinal Data from Meta-Analyses #MMPMID26697876 Cumming TB; Churilov L; Sena ES PLoS One 2015[]; 10 (12): ä PMID26697876show ga Background: Meta-analyses are considered the gold standard of evidence-based health care, and are used to guide clinical decisions and health policy. A major limitation of current meta-analysis techniques is their inability to pool ordinal data. Our objectives were to determine the extent of this problem in the context of neurological rating scales and to provide a solution. Methods: Using an existing database of clinical trials of oral neuroprotective therapies, we identified the 6 most commonly used clinical rating scales and recorded how data from these scales were reported and analysed. We then identified systematic reviews of studies that used these scales (via the Cochrane database) and recorded the meta-analytic techniques used. Finally, we identified a statistical technique for calculating a common language effect size measure for ordinal data. Results: We identified 103 studies, with 128 instances of the 6 clinical scales being reported. The majority? 80%?reported means alone for central tendency, with only 13% reporting medians. In analysis, 40% of studies used parametric statistics alone, 34% of studies employed non-parametric analysis, and 26% did not include or specify analysis. Of the 60 systematic reviews identified that included meta-analysis, 88% used mean difference and 22% employed difference in proportions; none included rank-based analysis. We propose the use of a rank-based generalised odds ratio (WMW GenOR) as an assumption-free effect size measure that is easy to compute and can be readily combined in meta-analysis. Conclusion: There is wide scope for improvement in the reporting and analysis of ordinal data in the literature. We hope that adoption of the WMW GenOR will have the dual effect of improving the reporting of data in individual studies while also increasing the inclusivity (and therefore validity) of meta-analyses. äThe Missing Medians: Exclusion of Ordinal Data from Meta-Analyses (epmc).pdf DeepDyve Pubget Overpricing