Forest plots: trying to see the wood and the trees

By Steff C. Lewis, M. Clarke. British medical journal, 2001

737 citations recorded by the source corpus.

Few systematic reviews containing meta-analyses are complete without a forest plot. But what are forest plots, and where did they come from? #### Summary points Forest plots show the information from the individual studies that went into the meta-analysis at a glance They show the amount of variation between the studies and an estimate of the overall result Forest plots, in various forms, have been published for about 20 years During this time, they have been improved, but it is still not easy to draw them in most standard computer packages In a typical forest plot, the results of component studies are shown as squares centred on the point estimate of the result of each study. A horizontal line runs through the square to show its confidence interval—usually, but not always, a 95% confidence interval. The overall estimate from the meta-analysis and its confidence interval are put at the bottom, represented as a diamond. The centre of the diamond …

Subfields: Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/768ce27765cae0ee33654442591b4cb2bf2af07b

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Citations in the corpus

If your P value looks too good to be true, it probably is: Communicating reproducibility and variability in cell biology (2019, methodology): “” Meta-analyses of multiple clinical trials often use estimation statistics and summarize multiple studies together into one “forest” plot (Lewis and Clarke 2001), which includes a summary value resulting from the metaanalysis (Deeks et al.”
Systematic review automation technologies (2014, methodology): “The most common way to summarize a meta-analysis is using a forest plot [129] but other plots exist, such as Galbraith diagrams (also called radial dia-”
Gender-Role Differences in Spatial Ability: A Meta-Analytic Review (2013, background): “A forest plot conveys a visual representation of the effect size estimates of individual studies and their variability (Lewis and Clarke 2001); one can see the amount of variation between individual studies as well as the overall trend.”
Displaying Uncertainty With Shading (2008, methodology): “In the forest plot commonly used to illustrate meta-analyses (Lewis and Clarke 2001) the size of the symbol plotted at the point estimate is usually varied in proportion to the weight given to the study in the combined estimate.”
Major Management Factors Determining Spring and Winter Canola Yield in North America (2018, methodology): “For the meta-analysis, a forest plot (Lewis and Clarke, 2001) was used to summarize the effect of each component evaluated.”
Estimation of the burden of active and life-time epilepsy: A meta-analytic approach (2010, methodology): “We used forest plots (Lewis & Clarke, 2001) to visualize the heterogeneity among the studies.”
Cochrane Handbook for Systematic Reviews of Interventions (2010, background): “Forest plots display effect estimates and confidence intervals for each individual study and the meta-analysis (Lewis and Clarke 2001).”