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

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

Description

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

Usage

## 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 <[e-mail]>

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

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.