print.netcomb {netmeta} | R Documentation |
Print method for objects of class netcomb
Description
Print method for objects of class netcomb
.
Usage
## S3 method for class 'netcomb'
print(
x,
common = x$common,
random = x$random,
backtransf = x$backtransf,
nchar.comps = x$nchar.comps,
digits = gs("digits"),
digits.stat = gs("digits.stat"),
digits.pval = gs("digits.pval"),
digits.pval.Q = max(gs("digits.pval.Q"), 2),
digits.Q = gs("digits.Q"),
digits.tau2 = gs("digits.tau2"),
digits.tau = gs("digits.tau"),
digits.I2 = gs("digits.I2"),
scientific.pval = gs("scientific.pval"),
zero.pval = gs("zero.pval"),
JAMA.pval = gs("JAMA.pval"),
big.mark = gs("big.mark"),
text.tau2 = gs("text.tau2"),
text.tau = gs("text.tau"),
text.I2 = gs("text.I2"),
legend = TRUE,
warn.deprecated = gs("warn.deprecated"),
...
)
Arguments
x |
An object of class |
common |
A logical indicating whether results for the common effects model should be printed. |
random |
A logical indicating whether results for the random effects model should be printed. |
backtransf |
A logical indicating whether results should be
back transformed in printouts and forest plots. If
|
nchar.comps |
A numeric defining the minimum number of characters used to create unique names for components. |
digits |
Minimal number of significant digits, see
|
digits.stat |
Minimal number of significant digits for z- or
t-value, see |
digits.pval |
Minimal number of significant digits for p-value
of overall treatment effect, see |
digits.pval.Q |
Minimal number of significant digits for
p-value of heterogeneity tests, see |
digits.Q |
Minimal number of significant digits for
heterogeneity statistics, see |
digits.tau2 |
Minimal number of significant digits for
between-study variance, see |
digits.tau |
Minimal number of significant digits for square
root of between-study variance, see |
digits.I2 |
Minimal number of significant digits for I-squared
statistic, see |
scientific.pval |
A logical specifying whether p-values should be printed in scientific notation, e.g., 1.2345e-01 instead of 0.12345. |
zero.pval |
A logical specifying whether p-values should be printed with a leading zero. |
JAMA.pval |
A logical specifying whether p-values for test of component or combination effect should be printed according to JAMA reporting standards. |
big.mark |
A character used as thousands separator. |
text.tau2 |
Text printed to identify between-study variance
|
text.tau |
Text printed to identify |
text.I2 |
Text printed to identify heterogeneity statistic
I |
legend |
A logical indicating whether a legend should be printed. |
warn.deprecated |
A logical indicating whether warnings should be printed if deprecated arguments are used. |
... |
Additional arguments (to catch deprecated arguments). |
Author(s)
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
See Also
Examples
data(Linde2016)
# Only consider studies including Face-to-face PST (to reduce
# runtime of example)
#
face <- subset(Linde2016, id %in% c(16, 24, 49, 118))
# Conduct random effects network meta-analysis
#
net1 <- netmeta(lnOR, selnOR, treat1, treat2, id,
data = face, reference.group = "placebo",
sm = "OR", common = FALSE)
# Additive model for treatment components
#
nc1 <- netcomb(net1)
nc1
print(nc1, digits = 2, digits.stat = 3)
## Not run:
# Conduct random effects network meta-analysis
#
net2 <- netmeta(lnOR, selnOR, treat1, treat2, id,
data = Linde2016, reference.group = "placebo",
sm = "OR", common = FALSE)
# Additive model for treatment components
#
nc2 <- netcomb(net2)
nc2
print(nc2, digits = 2, digits.stat = 3)
## End(Not run)