metaplus (version 1.0-5)

plot.metaplus: Produces forest plot for the studies together with the meta-analysis results.

Description

Produces a forest plot for the studies in the meta-analysis and the result of the meta-analysis. Allows the inclusion of extra results of alternative meta-analyses, to allow, for example comparison between standard and robust methods of meta-analysis. Makes extensive use of the metafor package to produce the forest plot.

Usage

# S3 method for metaplus
plot(x, ..., extrameta = NULL)

Value

Plot

Arguments

x

metaplus object to be plotted

...

additional parameters to plot

extrameta

Additional metaplus objects to be plotted. Only the summary statistic is plotted at the end of the plot. This is useful for comparing standard and robust methods, or meta-regressions for various values of the predictor.

Author

Ken Beath <[e-mail]>

Examples

# \donttest{
data(cdp)
# produce all 3 models for the CDP data and plot them all
cdp1 <- metaplus(yi, sei, plotci = TRUE, slab = study, cores = 1, data = cdp)
cdp2 <- metaplus(yi, sei, plotci = TRUE, slab = study, random = "t-dist", cores = 1, data = cdp)
cdp3 <- metaplus(yi, sei, plotci = TRUE, slab = study, random = "mixture", cores = 1, data = cdp)
plot(cdp1, extrameta = list(cdp2, cdp3))

# plot effect of exercise on depression at 4, 8 and 12 weeks
data(exercise)
exercise$duration4 <- exercise$duration-4
exercise$duration8 <- exercise$duration-8
exercise$duration12 <- exercise$duration-12

exercise.wk4 <- metaplus(smd, sqrt(varsmd), mods = duration4, 
 label = "Random Mixture (Week 4)", slab = study, random = "mixture", cores = 1, data = exercise)
exercise.wk8 <- metaplus(smd, sqrt(varsmd), mods = duration8, 
 label = "Random Mixture (Week 8)", slab = study, random = "mixture", cores = 1, data = exercise)
exercise.wk12 <- metaplus(smd, sqrt(varsmd), mods = duration12, 
 label = "Random Mixture (Week 12)", slab = study, random = "mixture", cores = 1, data = exercise)

exercise.nodurn <- metaplus(smd, sqrt(varsmd), plotci = TRUE, 
 label = "Random Mixture (No Duration)", slab = study, random = "mixture",
 cores = 1, data = exercise)

plot(exercise.nodurn, extrameta = list(exercise.wk4, exercise.wk8, exercise.wk12))
# }