What bias should be considered in meta-analysis and how do you display it?

• A. Publication bias with funnel plot
• B. Selection bias with forest plot
• C. Information bias with scatter plot
• D. Random error bias with histogram

Answer: (A)

Publication bias is a key concern in meta-analysis because studies with significant results are more likely to be published, which can skew the overall estimate. The standard way to display this bias is with a funnel plot. In a funnel plot, each study’s effect size is plotted on the horizontal axis and a measure of its precision (typically the standard error) on the vertical axis. Without bias and with low heterogeneity, the plot should look like a symmetrical inverted funnel: small studies spread widely at the bottom, and larger, more precise studies cluster near the top around the true effect.

If publication bias is present, the funnel becomes asymmetrical because small studies with non-significant results may be missing, causing a tilt or gap on one side of the plot. While other plots, like a forest plot, summarize study results, they don’t specifically display publication bias. Scatter plots or histograms are less direct for this purpose. The funnel plot is the conventional visualization used to assess potential publication bias in meta-analyses.