Forest plots are an important graphical method in meta-analyses used to show results from individual studies and pooled analyses. This visual representation also makes it easier to see variations between individual study results.
Why are forest plots important?
12.10. A forest plot is an essential tool to summarize information on individual studies, give a visual suggestion of the amount of study heterogeneity, and show the estimated common effect, all in one figure.
Forest plots are graphic displays that are used to illustrate individual and estimated group data from a meta-analysis of multiple quantitative studies that answer the same research question (Schriger et al., 2010).
How do you make a forest plot?
How to create a forest plot in ExcelCreate a clustered bar. First, highlight the first two columns containing the study name and the effect size. Add in the row positions. Add a scatter plot to your graph. Remove the clustered bar graph. Add error bars (whiskers) to the scatter points. Format the forest plot.
What is L Abbe plot?
The LAbbé plot (LAbbé, Detsky, and ORourke 1987) is a scatterplot of the summary outcome measure such as log odds in the control group on the x axis and of that in the treatment group on the y axis. The LAbbé plot explores between-study heterogeneity by comparing group-level summary outcome measures across studies.
How does a funnel plot work?
Funnel plots are a visual tool for investigating publication and other bias in meta-analysis. They are simple scatterplots of the treatment effects esti- mated from individual studies (horizontal axis) against a measure of study size (vertical axis).