Forest Plot Interpretation - Clearly Explained
Steven Bradburn・9 minutes read
Forest plots in meta-analyses display results from various studies, showing detailed information about participant numbers and effect sizes represented by squares or circles with confidence intervals. The size of squares corresponds to the weight of each effect size, and a diamond at the bottom represents the summary effect calculated after pooling individual study results.
Insights
- The forest plot in meta-analyses displays data from various studies, with each row showing study details and effect sizes represented by squares or circles.
- The size of squares in the plot corresponds to the weight of each effect size, with wider confidence intervals suggesting less precision, and the summary effect is represented by a diamond at the bottom, determined by pooled study results.
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Recent questions
What is a forest plot?
A forest plot is a figure commonly used in meta-analyses to display results from different studies, with each row representing data from a separate study.
What information is typically included in a forest plot?
A forest plot usually includes study names, publication years, participant numbers, effect sizes, and 95% confidence intervals for each study.
How are effect sizes represented in a forest plot?
Effect sizes in a forest plot are often depicted by squares or circles, with this example using squares to show standardized mean differences.
What do wider confidence intervals in a forest plot indicate?
Wider confidence intervals in a forest plot suggest less precision in the study results, while narrower intervals indicate more precise estimates.
How is the summary effect represented in a forest plot?
The summary effect in a forest plot is calculated by pooling individual study results and is represented by a diamond at the bottom of the plot, with its 95% confidence intervals determining significance.
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Summary
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Meta-analysis Forest Plot Visualizes Study Results
- Forest plot is a common figure in meta-analyses displaying results from various studies, with each row containing data from a different study.
- The left side of the plot typically shows study names and publication years, while each row includes detailed information about the study, such as participant numbers.
- Effect sizes from individual studies are represented by squares or circles, with this example using squares to show standardized mean differences.
- Horizontal lines on either side of the effect size indicate 95% confidence intervals, with wider intervals suggesting less precision.
- The size of squares in the plot corresponds to the weight of each effect size in the analysis, with larger squares indicating greater influence.
- The summary effect, calculated after pooling individual study results, is represented by a diamond at the bottom of the plot, with its 95% confidence intervals determining significance.
