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# Forest Plots

# Forest plots are used to display, on a single axis, the meta-analysis of multiple studies that test the same question using the same statistic. This statistic represents the effect size in studies, which are typically measured by the mean difference, odds ratio, risk ratio, or hazard ratio.

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# Breaking down the forest plot

# Forest plots display the values of the observed effect sizes found in the included studies using a black square, with the horizontal line through each square marking the 95% confidence interval. Each study is weighted based on its inverse variance and indicated by the size of the squares in the forest plot. The dotted vertical line, known as the "line of null effect", represents the case of no difference between the treatment and control interventions while the black diamond at the bottom of the "forest" marks the combined average outcome size for all of the studies.

# Forest plot

nstudy=10

se=y=NULL

set.seed(1234)

for (istudy in 1:nstudy){

se=c(se, runif(1, 0.1, 0.4))

y=c(y, rnorm(1, sd=se))

}

random = rma(y, sei=se)

forest(random)

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