plot.rma {metafor} | R Documentation |
Plot method for objects of class "rma.uni"
, "rma.mh"
, "rma.peto"
, and "rma.glmm"
.
## S3 method for class 'rma.uni' plot(x, qqplot=FALSE, ...) ## S3 method for class 'rma.mh' plot(x, qqplot=FALSE, ...) ## S3 method for class 'rma.peto' plot(x, qqplot=FALSE, ...) ## S3 method for class 'rma.glmm' plot(x, qqplot=FALSE, ...)
x |
an object of class |
qqplot |
logical to specify whether a normal QQ plot should be drawn (the default is |
... |
other arguments. |
Four plots are produced. If the model does not contain any moderators, then a forest plot, funnel plot, radial plot, and a plot of the standardized residuals is provided. If qqplot=TRUE
, the last plot is replaced by a normal QQ plot of the standardized residuals.
If the model contains moderators, then a forest plot, funnel plot, plot of the standardized residuals against the fitted values, and a plot of the standardized residuals is provided. If qqplot=TRUE
, the last plot is replaced by a normal QQ plot of the standardized residuals.
If the number of studies is large, the forest plot may become difficult to read due to the small font size. Stretching the plotting device vertically should provide more space.
Wolfgang Viechtbauer wvb@metafor-project.org https://www.metafor-project.org
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://doi.org/10.18637/jss.v036.i03
forest
for forest plots, funnel
for funnel plots, radial
for radial plots, and qqnorm.rma.uni
for normal QQ plots.
### calculate log risk ratios and corresponding sampling variances dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg) ### fit random-effects model res <- rma(yi, vi, data=dat) ### plot results plot(res, qqplot=TRUE) ### fit mixed-effects model with absolute latitude and publication year as moderators res <- rma(yi, vi, mods = ~ ablat + year, data=dat) ### plot results plot(res, qqplot=TRUE)