1/3/2023 0 Comments Revman 5 meta regressionLet us try out the drapery function in an example using our m.gen meta-analysis object. Either "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright", "right", or "center". Legend: Logical, indicating if a legend should be printed. Labels: When we set this argument to "studlab", the study labels will be included in the plot. If FALSE, only the summary effect is printed. Study.results: Logical, indicating if the results of each study should be included in the plot. This can be "zvalue" (default) for the test statistic, or the \(p\)-value ( "pvalue"). Type: Defines the type of value to be plotted on the y-axis. There are a few additional arguments, with the most important ones being: Overall, this allows others to quickly examine the precision and spread of the included studies, and how the pooled effect relates to the observed effect sizes. They also display the pooled effect we have calculated in a meta-analysis. Such plots provide a graphical display of the observed effect, confidence interval, and usually also the weight of each study. The most common way to visualize meta-analyses is through forest plots. We now come to a somewhat more pleasant part of meta-analyses, in which we visualize the results we obtained in previous steps. N the last chapters, we learned how we can pool effect sizes in R, and how to assess the heterogeneity in a meta-analysis.
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