Meta-analysis plot (forest plot)

Description

Plot confidence intervals with boxes indicating the sample size/precision and optionally a diamond indicating a summary confidence interval. This function is usually called by plot methods for meta-analysis objects. Additional, you can specifiy your own lower and upper boarder from the confidence interval.

Usage

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metaplot.surv(mn, se=NULL, lower=NULL, upper=NULL, nn=NULL,
    labels=NULL, conf.level = .95, xlab = "", ylab = "", xlim = NULL,
    summn = NULL, sumse = NULL, sumlower = NULL, sumupper = NULL,
    sumnn = NULL, summlabel = "Summary", logeffect = FALSE,
    lwd = 2, boxsize = 1, zero = as.numeric(logeffect),
    colors, xaxt="s", logticks=TRUE, ... )

Arguments

mn

point estimates from studies

se

standard errors of mn

lower

Vector of lower ends of confidence intervals

upper

Vector of upper ends of confidence intervals

nn

precision: box ares is proportional to this. 1/se^2 is the default

labels

labels for each interval

conf.level

Confidence level for confidence intervals

xlab

label for the point estimate axis

ylab

label for the axis indexing the different studies

xlim

the range for the x axis.

summn

summary estimate

sumse

standard error of summary estimate

sumlower

lower end of confidence intervals of summary estimate

sumupper

upper end of confidence intervals of summary estimate

sumnn

precision of summary estimate

summlabel

label for summary estimate

logeffect

TRUE to display on a log scale

lwd

line width

boxsize

Scale factor for box size

zero

"Null" effect value

xaxt

use "n" for no x-axis (to add a customised one)

logticks

if TRUE and logscale, have tick values approximately equally spaced on a log scale

.

colors

see meta.colors

...

Other graphical parameters

Value

This function is used for its side-effect.

See Also

forestplot.surv for more flexible plots

Examples

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metaplot.surv(mn=c(0.4,0.5,0.6), lower=c(0.35,0.4,0.57), upper=c(0.45,0.6,0.63), labels=c("A","B","C"), xlim=c(0.2,0.8), boxsize=0.5, zero=0.5, col=rmeta::meta.colors(box="royalblue",line="darkblue",zero="firebrick"))

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