"Metagraphiti By Stata": Visuographical Exploration and Presentation of Meta-analytic Data Using Stata
Meta-analysis is considered the highest level of evidence on effectiveness of healthcare interventions. It provides important information by capitalizing on the large numbers of studies performed to assess the impact of healthcare interventions, helps reduce variability and uncertainty among published reports of efficacy, produce summary estimates of effectiveness for clinical decision making and evaluate the quality of the published evidence. However, a large proportion of meta-analyses pose a surprising challenge for the uninitiated user: in order to figure out what the researchers found, the user must struggle through a maze of textual jargon, statistical formulae and lengthy lists of actual studies and extensive tables of overall average effect size and mean effect sizes for important subgroups of studies. On the premise that "a picture is worth more than a thousand words but a 'metagraphita' is worth more than a thousand words and statistical tests", the purpose of this presentation is to provide an idiot-proof overview of statistical graphics/diagnostic plots for exploration of publication bias, data distribution, heterogeneity and for summarizing overall datasets. Discussion will include the construction and interpretation of general graphical displays such as weighted histograms, normal quantile plots, forest plots, funnel graphs, scatter diagrams, as well as plots unique to diagnostic meta-analysis (e.g. ROC plane graphic, Accuracy-Threshold regression plots, summary receiver operator characteristic curves and likelihood ratio scattergrams). Presentation will consist of didactic slide presentation supplemented by handouts and an annotated bibliography and illustration of derivation and interpretation of visual displays from published meta-analyses using Stata.
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