## Is forest plot only for meta-analysis?

Graphical Depictions of Toxicological Data The forest plot is not necessarily a meta-analytic technique but may be used to display the results of a meta-analysis or as a tool to indicate where a more formal meta-analytic evaluation may be useful. An example of a forest plot is shown in Figure 4.

**How would you describe forest plot results?**

Each horizontal line on a forest plot represents an individual study with the result plotted as a box and the 95% confidence interval of the result displayed as the line. The implication of each study falling on one side of the vertical line or the other depends on the statistic being used.

**How do you interpret the p value in a forest plot?**

More information is found at the lower left corner of the plot. The p-value indicates the level of statistical significance. If the diamond shape does not touch the line of no effect, the difference found between the two groups was statistically significant. In that case, the p-value is usually < 0.05.

### What is a good I2?

It can take values from 0% to 100%. If I^2 ≤ 50%, studies are considered homogeneous, and a fixed effect model of meta-analysis can be used. If I^2 > 50%, the heterogeneity is high, and one should usea random effect model for meta-analysis.

**How do you set up data for a meta-analysis?**

All meta-analytic efforts prescribe to a similar workflow, outlined as follows:

- 1) Formulate research question.
- 2) Identify relevant literature.
- 3) Extract and consolidate study-level data.
- 4) Data appraisal and preparation.
- 5) Synthesize study-level data into summary measure.
- 6) Exploratory analyses.
- 7) Knowledge synthesis.

**What are forest plots used for?**

Forest plots are an important graphical method in meta-analyses used to show results from individual studies and pooled analyses.

#### Why do we use forest plot?

Forest plots are easy and straightforward to understand because they provide tabular and graphical information about estimates of comparisons or associations, corresponding precision, and statistical significance. This visual representation also makes it easier to see variations between individual study results.

**How do you read a forest plot statistics?**

**What is a good i2?**

## What is p-value in meta-analysis?

P values are used as the means of converting meta-analysis results to defined/known test statistics which are expressible as a function of the estimates of the βs and σs described above.

**Is high heterogeneity good or bad?**

Having statistical heterogeneity is not a good or bad thing in and of itself for the analysis; however, it’s useful to know to design, choose and interpret statisti- cal analyses. Indeed, the comparison of heterogeneity often will be the outcome of interest, especially in quality fields.

**What is I2 in a forest plot?**

The I^2 indicates the level of of heterogeneity. It can take values from 0% to 100%. If I^2 ≤ 50%, studies are considered homogeneous, and a fixed effect model of meta-analysis can be used. If I^2 > 50%, the heterogeneity is high, and one should usea random effect model for meta-analysis.

### How many papers do you need for a meta-analysis?

Two studies

Two studies is a sufficient number to perform a meta-analysis, provided that those two studies can be meaningfully pooled and provided their results are sufficiently ‘similar’.

**How do you present meta-analysis data?**

The typical graphic displaying meta-analysis data is a Forest plot, in which the point estimate for the risk ratio is represented by a square or circle and the confidence interval for each study is represented by a horizontal line.