plot.riley: Plot the summary of the bivariate model from Riley et al....

Description Usage Arguments Author(s) References Examples

View source: R/riley.r

Description

Generates a forest plot for each outcome of the bivariate meta-analysis.

Usage

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## S3 method for class 'riley'
plot(x, title, sort = "asc", xlim, refline, ...)

Arguments

x

An object of class riley

title

Title of the forest plot

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.

xlim

The x limits (x1, x2) of the forest plot

refline

Optional numeric specifying a reference line

...

Additional parameters for generating forest plots

Author(s)

Thomas Debray <thomas.debray@gmail.com>

References

Riley RD, Thompson JR, Abrams KR. An alternative model for bivariate random-effects meta-analysis when the within-study correlations are unknown. Biostatistics 2008; 9: 172–186.

Examples

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data(Scheidler)

#Perform the analysis
fit <- riley(Scheidler[which(Scheidler$modality==1),])
plot(fit)

require(ggplot2)
plot(fit, sort="none", theme=theme_gray())

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