Learning how to interpret meta-analysis

Meta-analysis is interpreted using multiple types of data and the associated plots. By far the most important part of the meta-analysis workflow is interpreting forest plots.

Interpreting forest plots

Have a look at the following figure:

Figure 12.10 – Typical representation of a forest plot in a meta-analysis

As you can see, the forest plot looks like a tree, and that is where its name came from. The tree consists of individual studies and the overall effect. When interpreting forest plots, it is never a good idea to jump to the final overall effect conclusions. Start by looking at the individual studies and see how they relate to each other. Are they similar in the point estimates, central points, and confidence intervals?

Then, look at the heterogeneity, which is a number below the plot telling us how heterogeneous the results of the studies are. This can be seen by observing the boxes in reference...