Plot the summary of the bivariate model from Riley et al. (2008).

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

Usage

# S3 method for 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

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.

Author

Thomas Debray <thomas.debray@gmail.com>

Examples

data(Scheidler)

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


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