plot.uvmeta: Forest Plots

In metamisc: Meta-Analysis of Diagnosis and Prognosis Research Studies

Description

Function to create forest plots for objects of class "uvmeta".

Usage

## S3 method for class 'uvmeta'
plot(x, sort = "asc", ...)

Arguments

x	An object of class "uvmeta"
sort	By default, studies are ordered by ascending effect size (sort="asc"). For study ordering by descending effect size, choose sort="desc". For any other value, study ordering is ignored.
...	Additional arguments which are passed to forest.

Details

The forest plot shows the performance estimates of each validation with corresponding confidence intervals. A polygon is added to the bottom of the forest plot, showing the summary estimate based on the model. A 95% prediction interval is added by default for random-effects models, the dotted line indicates its (approximate) bounds

Note

Full lines indicate confidence intervals or credibility intervals (in case of a Bayesian meta-analysis). Dashed lines indicate prediction intervals. The width of all intervals is defined by the significance level chosen during meta-analysis.

Author(s)

Thomas Debray <[e-mail]>

References

• Lewis S, Clarke M. Forest plots: trying to see the wood and the trees. BMJ. 2001; 322(7300):1479–80.

• Riley RD, Higgins JPT, Deeks JJ. Interpretation of random effects meta-analyses. BMJ. 2011 342:d549–d549.

Examples

data(Roberts)

# Frequentist random-effects meta-analysis
fit <- with(Roberts, uvmeta(r=SDM, r.se=SE, labels=rownames(Roberts)))
plot(fit) 

metamisc documentation built on Oct. 13, 2021, 3 p.m.